International Journal of Networking and Virtual Organisations (92 papers in press)
The Co-Evolution of IT Competence, Organisational Agility and Entrepreneurial Action: A Case Study of Entrepreneurial E-tailers
by Shan Wang, Youwei Wang, Norm Archer
Abstract: Due to the turbulent business environment, small and medium-sized e-commerce companies tend to adopt a strategic logic that requires the support and co-evolution of organisational agility capability and Information Technology (IT) competence. However, the characteristics of organisational agility and IT competence and their co-evolution mechanisms are largely unknown. Based on the Sambamurthy et al. (2003). theoretical framework about the strategic logic for firms in a turbulent business environment, we undertook a case study of ten entrepreneurial e-tailers (re-tailers selling primarily on the Internet) on a third party Chinese e-commerce platform. From these firms we identified the characteristics and the evolutionary path of entrepreneurial actions, organisation agility and IT competence for small and medium-sized entrepreneurial actions, organisation agility and IT competence from the perspective of real options and adaptive learning. This research advances our current understanding of SME e-commerce firm strategic logic and required firm capabilities.
Keywords: entrepreneurial action, organisational agility, IT competence, adaptive co-evolution, real options, adaptive learning
Data Analysis to Uncover Critical Parameters for Performance Appraisal of Students in Higher Education
by Raju Ranjan, Jayanthi Ranjan
Abstract: Performance of students sometimes gives the most committed, knowledgeable, well-intentioned teacher wondering what is wrong with his/her class or a particular student. The growing demand of information which will provide assistance to decision makers in appraisal of a students performance is guiding a path towards extensive usage of analytical tools for revealing hidden information. The intelligent information from the data of higher education provides hidden information and pattern from students data, and thus helps in performance appraisal in the academia which will provide avenues for overall growth of the students in the higher education field. The authors through this paper highlighted the methodology to be adapted in reduction of the various available critical parameters and thus identified the key critical parameters for the performance evaluation of the students in higher education. The authors classified the collected data variables into broad categories and applied the Data Mining techniques to uncover the critical parameters in higher education.
Keywords: Cumulative Grade Point Average, Data Analytics, Data Mining, Artificial Neural Network
Examining Users Switch from Online Banking to Mobile Banking
by Tao Zhou
Abstract: As an emerging service, mobile banking has received minor adoption among users. This may be for the reason that they are locked into the relationship with online banking and are unable to switch from online banking to mobile banking. Integrating both perspectives of enablers and inhibitors, this research examined users switch from online banking to mobile banking. Enablers include relative advantage, perceived ease of use, trust, flow and social influence, whereas the inhibitor is switching costs. The results indicated that switch intention is affected by both enablers and inhibitors. Among them, flow and switching costs have the largest effects. This research provides a new perspective (switch behavior) of examining mobile banking user behavior, which has been mainly tested from technology adoption perspective.
Keywords: online banking; mobile banking; switch intention; trust.
Virtual resource pricing scheme in cloud platforms
by Ying Hu, Ze Xiao
Abstract: Recently, economic model has been widely applied in cloud platforms for regulating virtual resource sharing. In the economic model, resource pricing scheme plays a key role for managing the relationship between cloud users and cloud providers. In this paper, we present a novel pricing scheme for virtual resource provision with aiming at improving resource utilization and reducing operational costs for cloud providers. Unlike previous studies, the proposed pricing scheme applies Producer-Retailer-Client model to describe the procedure of virtual resource trade and provides the optimal pricing solution by using gaming theory. Extensive experiments are conducted in a real-world cloud platform, and the results demonstrate that the proposed pricing scheme outperforms other approaches in terms of the increased profit and the reduction of variance of virtual resource prices.
Keywords: virtual resource; quality of service; pricing scheme; load balance
The Application of Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation in the Evaluation of Ecological Security in Coal Mine Areas
by Xiaoling Ke, Min Feng, Meng Xiang
Abstract: This article researches the current condition and problems of ecological security in coal mine areas. It adopts the pressure, status and response (P-S-R) model as its framework, establishes a coal mining area ecological security evaluative index system, which is divided into three layers: the target layer is ecological security status, the principle layer is the pressure, status and response of ecological security, the solution layer contains the corresponding measuring indices (altogether twenty seven). It then adopts AHP (Analytic Hierarchy Process) and fuzzy comprehensive evaluative method to establish an evaluative index model of coal mining area ecological security. It first calculates the weights of various factors in the model by AHP and then concludes the model evaluation by fuzzy comprehensive evaluation. This article uses a coal mine of a Zhengzhou coal mining group as the object of analysis, conducts questionnaire and interview, and then applies the model established by this article to evaluate its ecological security, which results in a V3 level (ordinary level) in its ecological security.
Keywords: Analytic Hierarchy Process; Fuzzy Comprehensive Evaluation; Ecological Security; Coal Mining Area.
An energy-efficient frequency scaling technique for virtualized memory in clouds
by Peng Xiao, Yuan Tian
Abstract: As more and more non-trivial applications have been deployed on cloud platforms, the energy consumption in cloud-based datacenters has become a critical issued that needs to be addressed. In previous studies, most of researchers focused on improving the CPU-related energy conservation approaches while few of them take efforts on memory-related energy saving techniques. In this paper, a novel memory energy saving mechanism called frequency scaling on virtualized memory is proposed, which uses the dynamical voltage frequency scaling on memory component so as to adjust the working power of a virtualized servers memory based on the runtime characteristics of active virtual machines. In this way, the proposed mechanism can provide a fine-grained energy conservation mechanism for those virtualized servers in cloud platforms. In the experiments, we extensively investigate the effectiveness and performance of the proposed mechanism on various kinds of servers and workloads. The experimental results show that it can significantly improve the energy-efficiency of memory subsystem in virtualized servers.
Keywords: cloud computing; virtualized memory; frequency scaling; energy-efficiency
Mobility Aware MAC Protocol for Providing Energy Efficiency and Stability in Mobile WSN
by G. Lakshmi Vara Prasad, T. Nalini, Sugumar R
Abstract: MWSNs need an efficient handling of mobility in all layers with respect to the sensor network protocol stack. The requirement to handle mobility adds another dimension to sensor network protocols, in addition to conservation of energy and computation resources. Accordingly we propose to design a Mobility Aware MAC Protocol for Providing Energy Efficiency and Stability for MWSNs. Initially a link status history is maintained while the MOX-MAC nodes send their data to static nodes. From this the link quality issue is addressed. If the link quality is poorer the MoX- MAC will drop or ignore the packet. Next in case of energy consumption the nodes enter into the periodic sleep-awake duty cycle. If the link quality is less than the threshold value, the corresponding communication is blocked.
Keywords: MWSN; MAC Protocol ;Efficiency and Stability ;MoX- MAC .
The Measurement of Gas Solid Two-phase Flow Parameters Based on Electrical Capacitance Tomography Technology
by Haijun Tian, Yunlong Zhou, Ting Yang, Yanghui Zhao
Abstract: In order to realize visualization measurement of gas-solid two phase flow parameters, a gas-solid two phase flow test-bed was developed. Polypropylene particles select as the solid phase, the air select as the gas phase. Solid phase rely on their own gravity flow through experimental device. M3C capacitance tomography device of ITS Company is used for test and research solid phase concentration, speed, mass flow rate about gas-solid two phase flow parameters. Concentration measurement is based on the dielectric constant distribution of the pixels about image. Capacitive sensor was used to measure velocity with double layer structure. The relevant principles of measurement speed were used to compute the correlation of downstream sensor imaging pixel. Finally, his mass flow was calculated by the measured velocity and concentration distributions. The Mass flow measurements were compared with the results of gravity sensor, and the results showed good agreement, measurement error was less than 10%. Experimental results show that the capacitance tomography system can be used to measure gas-solid two phase flow parameters.
Keywords: image; two-phase flow; mass flow; solid concentration; concentration; volume flow.
EVRC: an economic-based virtual resource co-allocation middleware for clouds
by Tienan Zhang
Abstract: In cloud platforms, resource co-allocation service plays an important role on meeting users requirements especially for running some large-scale applications, which typically need to be deployed on several virtual organizations. In this paper, we present an Economic-based Virtual Resource Co-allocation (EVRC) middleware, which provides a set of flexible services that allows cloud applications co-allocating plenty of virtual resources across different resource providers. In the EVRC framework, resource co-allocation service is implemented by a novel auction mechanism, and cloud users quality-of-service (QoS) requirements are guaranteed by a set of services including resource reservation, reputation manager and etc. In addition, the proposed EVRC middleware is incorporated with an online performance monitoring and profiling mechanism, which can be used to evaluate the efficiency of underlying resources and adjust up-level resource management policy. Extensive experiments are conducted to investigate the effectiveness of the EVRC middleware, and the results indicate that it can significantly improve the efficiency of virtual resource co-allocation as well as cloud users QoS satisfactory.
Keywords: cloud computing; virtualization; co-allocation; resource market
Fuzzy Based Trusted Security for Mobile Grid Systems
by Kavitha Bharathi S., S. Vegataasalam
Abstract: In Mobile Grid System, the main factor to be considered while deploying in real world application is security. Otherwise, the framework would be incomplete and impractical. In order to provide full security, successful job execution and high resource availability, in this paper, we propose to design a fuzzy based trusted security for mobile grid systems. In this technique, the trust index value of each node is estimated using fuzzy logic. Here the metrics grid residence time, reputation and degree of maliciousness are considered as input for the fuzzy logic and the trust index value is determined as output. Based on the trust index, GS allocates the grid node when it receives the service request. Also, as the trust index is calculated and updated by the GS, the malicious nodes cannot modify or destroy the values. By simulation results, we show that the proposed technique offers high security and high resource availability.
Keywords: Mobile Grid System;real world application ;trusted security;fuzzy logic.
Does social networking ultimately sustain organizational performance?
by Trong-Thuy Tran
Abstract: This study examines how integrated social networking sites (SNS) affect organizational management orientation (OMO) and assesses how this relationship can have an impact on managerial performance and organizational value. The researchers conducted a questionnaire and in-depth pilot interview to obtain the data with samples being selected from a developed economy (Taiwan) and an emerging economy (Thailand) with pretest. Non-respondent bias and common method variance were tested and the model was constructed by assessing reliability, extracting average variance, and testing discriminant validity. To test the proposed hypotheses, the researchers adopted PLS procedure. SNS integration appeared to strongly affect OMO, and managerial performance mediated the relationship between OMO and organizational value in both the developed and emerging economies. Interestingly, while no direct link could be established between OMO and organizational value in the developed economy, the researchers found that OMO appears to directly affect organizational value through managerial performance in the emerging economy.
Keywords: social networking site integration; organizational management orientation; managerial performance; organizational value
Adaptive Modulation and Interference Cancellation Techniques for MIMO-OFDM Wireless Networks
by Ali M. A, E. A Jasmin
Abstract: MIMO-OFDM (Multiple-input multiple-output antenna-Orthogonal Frequency Division Multiplexing) is one of the most wanted wireless broadband technology and transmission system that has been accepted as the basis of fourth generation (4G) wireless communication is MIMO-OFDM. It is so flexible and adaptable to stay in power even in the coming up 5G technologies. The relative motion of the transmitter and receiver can bring alteration in the channel within the time period of an OFDM, hence OFDM causes loss of orthogonally between sub carrier which results in inter-carrier interference. In order to overcome these issues, an Adaptive Modulation and Interference Cancellation Technique for MIMO-OFDM Wireless Network are proposed. Along with Interference cancellation technique, Adaptive Modulation is used to meet the required BER performance by selecting suitable modulation modes based on the channel condition. Doppler assisted channel estimation method is used to estimate the channel. Also, inter channel/carrier interference (ICI) cancellation scheme is used to integrate the Parallel Interference Cancellation together with the Decision Statistical Combining (PIC-DSC) module to detect the data and transmit it to the estimator to iteratively refine the channel and give interference free channel. Simulation results shows that the proposed method improves the BER performance of the system
Keywords: OFDM;MIMO;Wireless Network;Adaptive Modulation
Ant Based Self-healing Routing for Enhancing Lifetime of Wireless Sensor Networks
by Chaganti B Lakshmi, S. Krishana Mohan Rao
Abstract: In Self Healing Routing (SHR), receivers autonomously decide whether to forward the packet using only knowledge of their hop distances of the destination but neither energy estimation nor residual battery power is analyzed. Hence, failure may occur on the intermediate nodes causing the data loss in transmission. To overcome the disadvantages of SHR and enhance the lifetime of WSN, self-healing routing using Ant Colony Optimization (ACO) is proposed. In our proposed solution, the RREQ and RREP procedures are executed by the Forward Ant (FANT) and Backward Ant (BANT) respectively using ACO technique. Source node broadcast a FANT to the neighboring nodes along the destination which collects the hop distance and residual energy of each node. The next hop is selected based on the probability of pheromone. On reaching the destination, a BANT is transmitted through the reverse path. The collected hop distance and residual energy of each node by the BANT is analyzed at the source. By simulation results, we show that the Ant based self-healing routing reduces the delay and energy consumption while increasing the packet delivery ratio.
Keywords: Self Healing Routing; Ant Colony Optimization; packet delivery ratio.
A novel virtual machine scheduling policy based on performance prediction model
by Dongbo Liu, Yongjian Li
Abstract: In cloud platforms, virtual machine scheduling policy plays an important role for providing desirable service quality for users. In many existing scheduling policies, the task execution time is often assumed to be constant or defined by users. However, either unpredictable workload or resource unreliability may significantly affect task execution time, which in turn results in inefficient scheduling decisions. In this paper, we first present a task execution time model by applying queue theory; then we use this model to predict the performance of application at runtime and propose a novel virtual machine scheduling policy. By conducting extensive experiments, we investigate the effectiveness and efficiency of the proposed scheduling policy. The experimental results indicate that it can significantly reduce the response time of cloud application comparing with other existing scheduling policies.
Keywords: cloud; virtual machine; performance prediction; scheduling algorithm.
Prediction in Mobile Ad Hoc Network Based on Fuzzy Time Series
by Chunyu Yang
Abstract: Several parameters like routing protocol, mobility pattern, average speed of mobile nodes, path length from source to destination, previous delay, etc., affect the end-to-end packet delay in mobile ad hoc network. But the nature of relationship between end-to-end delay and those parameters is still unclear. The end-to-end delay can represented as a fuzzy time series. In this paper, a new method to forecast the end-to-end delay is presented. The method fully capitalizes on the two key technologies, automatic clustering and automatically generated weights, to handle the forecasting problems. First, the automatic clustering algorithm is utilized to generate clustering-based intervals. Then, the variation magnitudes of adjacent historical data are used to generate fuzzy variation groups. Third, the final forecasted variation can be obtained by the weights of the fuzzy variation. Finally, the phase of forecasting is performed. Based on performance evaluation criterion, we found that the predicted value of the proposed method gives satisfactory packed delay prediction in ad hoc network.
Keywords: Mobile Ad Hoc Network; Fuzzy Time Series; Fuzzy Forecasting; Automatic Clustering.
An accuracy-enhanced cost model for virtual machine migration
by Tienan Zhang
Abstract: In cloud platforms, virtual machine migration has become an important service which enables cloud providers to flexibly apply various resource management policies, such as elastic resource provision, load balance, server consolidation and etc. However, the cost of migrating a virtual machine still remains very high even by using the most efficient migration algorithm. More importantly, many studies have indicated that improperly using migration service will lead to significantly performance degradation in cloud environments. In this paper, we present a cost model for quantitatively evaluate the cost of virtual machine migration with aiming at providing an accurate and effective approach to improving the efficiency of current migration service. The proposed model only relies on the information that can be easily obtained from the underlying virtualization platform, which makes it can be conveniently implemented and deployed in cloud-based datacenters. To investigate the effectiveness and accuracy of the cost model, plenty of experiments are conducted by using various of standard benchmarks. The results show that it can significantly improve the accuracy comparing with existing models. In addition, the proposed model also exhibits better robustness and adaptiveness in presence of those workloads with distinctive characteristics.
Keywords: virtual machine; live migration; cost model; benchmark.
Improving scheduling efficiency by probabilistic execution time model in cloud environments
by Peng Xiao, Dongbo Liu, Kaijian Liang
Abstract: Recently, cloud computing has become a promising paradigm for various kinds of large-scale applications. Due to the unpredictable characteristics of resource availability and workload intensity, execution latency still drastically impairs the performances of cloud applications. In this paper, we model the execution latency by a probabilistic distribution and propose a general task execution model which can be used in most of scenarios. By using the proposed execution time model, cloud administrators can easily refine their resource management or implement some fine-grained task scheduling policies for cloud applications in various cases. Massive experiments are conducted in a real-world cloud platform, and the results indicate the proposed model can be used in many existing scheduling policies for improving the efficiency of task execution.
Keywords: cloud computing; resource virtualization; virtual machine; task scheduling.
Priority Based Bandwidth Allocation and Load Balancing For Multipath IP Networks
by Rekha V, Indiramma M
Abstract: Frequent route failures are common in a multipath IP (Internet Protocol) network. Backup configuration is one of the techniques used to re-establish alternate path in case of route failure. The existing Multi Route Configurations (MRC) for fast IP network does not address Quality of Service (QoS) issues such as Bandwidth optimization and Load balancing with traffic shaping. There is a need to focus on priority based routing and load balancing during congestion in multipath networks. In this paper, we are proposing a Priority Based Bandwidth Allocation and Load Balancing (PBALB) approach for multipath routing. In order to reduce packet drop and to enhance fairness, throughput and lower delay transmissions, traffic shaping based on different type of traffic flows in Differential service domain is proposed. Experimental result shows that the proposed PBALB technique improves the throughput compared to MRC.
Keywords: IP; QoS; Bandwidth Optimization; Compression; Load Balancing; Fairness,Priority; Scheduling.
Fuzzy Logic Based Optimized Algorithm for Mobility Robustness and Load-Balancing in LTE/4G networks
by Tanu Goyal, Sakshi Kaushal, Arun Kumar Sangaiah
Abstract: With the development of new mobile communication system, telecom operators requires planning, installation, testing, pre-post optimization, monitoring, evaluation and mitigation of failure of network. All these are complicated tasks and require number of workers, costly in nature, error- insensitive, customers dissatisfaction, etc. 3GPP Release 8 for LTE defined Self-Organizing Network (SON) to maximize efficiency in planning, deployment and maintenance by doing operations automatically. Industry has identified load balancing and handover optimization as two keys for self organizing mechanisms in a network. Although, most effort in literature have been made for single entity SON and Coordinate SON. In this paper, an algorithm based on joint optimization has been proposed using fuzzy logic and Partial Observed Markov Decision Process (POMDP). This algorithm optimizes the Key Performance Indicators (KPI), i.e., Call Block Rate (CBR), Call Drop Rate (CDR) and Handover Ratio (HOR) that are related to load balancing and handover optimization. The results are numerically analyze and the proposed algorithm improves overall network performance and hence users will get better Quality of Service (QoS).
Keywords: Joint Optimization; Partial Observed Markov Decision Process; Handover Optimization; LTE.
Contemporary Digital Business Model Decision Making: A Cloud Computing Supply-Side Perspective
by Trevor Clohessy, Thomas Acton, Lorraine Morgan
Abstract: Cloud computing is an example of a promising technological paradigm which possesses the potential to act as a catalyst to drive radical innovations in the development of the networked society. While some information and communication technology (ICT) providers have reaped the rewards by transitioning from antiquated hardware and service provision to more propitious cloud-based service provision methods, others have experienced substantial difficulties related to the formulation and operationalization of effective business models. This paper presents a research framework which can serve as a lens for exploring how digital organizations can execute their core business model decisions along increasingly specific decision making levels. Taking the perspective of an exemplar established large ICT provider, our study uses the research framework in order to provide new insight for facilitating cloud computing supply-side business model effectiveness.
Keywords: Business Model; Decision Making; Cloud Computing; ICT Provider.
Smart Phones and Surgeons: Privacy and legal issues in Australian healthcare
by Victoria Garwood, Damian Claydon-Platt, Nilmini Wickramasinghe, John Mackay, Phillip Smart
Abstract: Background: Smart phone use is both widespread and increasing in healthcare, bringing benefits to clinicians, patients and health systems, with the potential to revolutionise many aspects of clinical care. However, advances in camera and video capturing as well as automated uploading and sharing can result in patient privacy breaches by default. We aimed to review current Australian government legislation as well as hospital, legal and industry body guidelines in order to clarify best practice, and identify technological solutions that satisfy the needs of both patients and clinicians alike. Methods: Victorian health services with over 200 inpatient beds, metropolitan hospitals with emergency departments, industry regulators and professional bodies as well as all Australian Medical Indemnity insurers were surveyed regarding clinical photography policies, which then were assessed for adherence to current privacy legislation. Results: The majority of health services surveyed did not have a policy that appropriately addressed smart phone use by clinicians and current privacy legislation. Where smart phones use was addressed, use was typically banned or allowed with incomplete guidelines non-compliant with current privacy legislation. Conclusion: There is an urgent need to develop policies that recognise the ubiquity of smart phone use in modern healthcare, foster their potential to enhance patient care as well as reduce cost, yet rigidly protect patient privacy.
Keywords: Privacy; Cell Phones; Photography; Mobile Health; Mobile Applications.
Research On Network Design and Analysis of TGO Topology
by Shanmuk Srinivas Amiripalli
Abstract: In defense and similar kind of areas, usually we come across situations where the whole strategy cannot be identified by all the levels of subordinates in the hierarchy but can be shared by a cluster of officials in the sector. we address this problem in our previous research and we introduced a new graph called TRIMET and discussed its properties and scope. As the TRIMET having a wide range of applications in computers, electronics and military operations. We are extending our research work by converting TRIMET graph into a novel topology called TGO(TRIMET Graph Optimization) followed by TGO based network model.Finally, comparisons of TGO with star topology was done in NS2 simulator and theoretical analysis of TGO topology was done with standard parameters of network sciences.
Keywords: TRIMET,semi-complete graph; hierarchical model,BARABASI-ALBERT model; Random network model; scale-free network model; topology,graph optimization,Network sciences,network analysis.
Cloud Computing Security: Attacks, Threats, Risk & Solutions
by Shweta Kaushik, Charu Gandhi
Abstract: Cloud computing started a new promising era in the field of information technology, which has a new direction for the use of resources more efficiently within the least amount of payment. It becomes a center of attraction for many organizations like academic, healthcare, social etc. It allows the users to use the resources dynamically according to their requirements from any remote location using the Internet connection. Users can store huge amount of their data over the cloud environment and did not bother about its maintenance. Most of data over cloud is highly sensitive/ confidential in nature. For example: social data which include personal information, pictures and medical record of patients. But one of the biggest challenges in cloud computing is to provide the security and privacy of data to prevent it from any malicious attack. Security and privacy are thus, gaining important consideration to be solved in cloud system. Users must authenticate themselves before accessing any data or transaction to prove its validity against the required service. It must also be ensured that the cloud does not tamper with data that is outsourced . Many researchers addressed various cloud security requirements such as confidentiality, authentication, integrity etc. in their work, but it is difficult to understand that which security requirements have been solved more efficiently, and which are still not solved and lacking behind to investigate. In this paper, we discuss the various possible attacks, threats and security concerns with the possible countermeasures that need to be understood related to the cloud services. The current research also investigates that how different cloud frameworks are affected by which network attacks.
Keywords: Attacks; Cloud Computing; Infrastructure as a Service; Platform as a Service; Risks; Security; Software as a Service; Threats.
Location-Based Clustering and Collaborative Filtering for Mobile Learning
by Mohammad Alnabhan
Abstract: This paper presents a new m-learning model described as Location-based Collaborative M-learning (LCM). This new model exploits location information of mobile users and implements two main operations; k-means for clustering mobile users, and location-based Collaborative Filtering (CF) to provide learning items recommendations to clustered users. A comprehensive evaluation methodology was utilized to validate the proposed model in terms of complexity, performance and learning items recommendations quality. Results have confirmed successful implementation of the proposed LCM model during different mobile users settings. It was shown that LCM structure efficiently reduces processing overload and time required for users' clustering and learning content authoring, and improves learning items recommendations accuracy.
Keywords: M-learning; Collaborative filtering; Clustering; Context; Location-Based.
Optimal Neural Network to Enhance Classification Accuracy for Mining Online Reviews and Opinions using Improved PSO
by B. Dhanalakshmi, A. Chandrasekar
Abstract: While using rapid growth from the World Wide Web there is volatile improve in the user-produced subject matter such as purchaser evaluations, websites, discussion community forums, social networks and so forth. Most of the subject matter tends to be located as such as unstructured or even partial structured data through in which distillation regarding knowledge is often a difficult undertaking. In the previous work, we have implemented opinion mining using three phase. They are 1) Data Preprocessing, 2) Opinion extraction and 3) Opinion mining. In Feature extraction, features such as term frequency, Part of Speech (POS), Syntax, Negation and Term-based features beyond term unigrams were extracted from the words in the documents. This final phase was done by supervised learning algorithm decision tree algorithm with the help of features extracted. In the final step ranking and classification was done. In the present work we will implement the same three phases as the previous work but with a different process in each of the following steps such as 1) Data Preprocessing 2) Opinion extraction 3) Opinion mining. This phase is used for formatting the data before sentiment analysis and mining. The second phase will be classified into two i.e., Feature extraction and opinion extraction. The features like term frequency, Part of Speech (POS), Syntax, Negation and Term-based features beyond term unigrams are extracted from the words in the documents. After feature extraction, we extract useful information related to the items features and use it to rate them as positive, neutral, or negative. This final phase will be done by Improved PSO optimized artificial neural network with the help of features extracted. The weights assigned in the artificial neural network will be optimized using Improved PSO algorithm. Weight optimization is done in order to improve the classification accuracy. In the final step ranking based on classification will be done. The performance measures will be evaluated and will be compared with our previous method in order to prove our proposed method in terms of accuracy.
Keywords: Artificial neural network; Improved PSO algorithm; Decision tree algorithm; Opinion extraction; Opinion mining.
Adaptive Priority Based Fair-Resource Allocation for MIMO-OFDM Multicast Networks
by V. Hindumathi, Katta Rama Linga Reddy
Abstract: In MIMO-OFDM Multicast Networks, sub-carrier allocation for real-time and non-real time users is complex due to delay and throughput issues. In order to overcome these issues, in this paper, we propose to develop a priority based fair-radio resource allocation for MIMO-OFDMA based multicast system. Initially, the multicast groups are classified as RT, NRT and BE. Then priorities are assigned for the groups based on the QoS requirements such as delay tolerance, packet dropping rate and transmission rate. When the priority value of a group is greater than the priority threshold, then the resource is allocated to the relevant group as per fair resource allocation technique. Overall this technique improves the sub-carrier allocation for real-time and non-real time users in terms of spectral efficiency and fairness. By simulation results, we show that the proposed technique enhances the Average throughput, spectral efficiency, sub-carrier distribution for each class of users.
Keywords: MIMO-OFDM Multicast Networks; QoS; (4G) wireless communication; resource allocation.
A multi-policy adaptive scheduling framework in virtual clouds
by Changsong Liu
Abstract: With the development of cloud computing technology, many cloud-based datacenters are beginning to connect with each other aiming at building large-scale federated cloud platforms. In such a federated cloud platform, the efficiency and effectiveness of traditional schedulers will be significantly degraded due to the unpredictable resource availability and high networking latency. In this paper, we propose a multi-policy adaptive scheduling framework, which is capable of evaluating the scheduling scheme made by existing schedulers. In this way, the proposed scheduling framework can make full use of the advantages of existing scheduling policies and avoid their shortcomings, and therefore makes the final scheduling decisions more efficient and effectiveness. In addition, the proposed scheduling framework is designed as extensible component that can be easily extended by incorporating other scheduling policies. The prototype of this scheduling framework is tested in a real-world federated cloud platform. The experimental results show that it can significantly improve the quality-of-service for the underlying cloud infrastructures as well as cloud users satisfactory.
Keywords: task scheduling; virtual organisation; cloud computing; load balance.
IT-enabled Inter-organizational Relationships and Collaborative Innovation: Integration of IT Design and Relationships Governance
by Fei Wang, Jing Zhao, LeWei Hu
Abstract: Firms developing collaborative innovation from IT-enabled inter-organizational relationships (IORs) are faced with both technological and relational challenges. Drawing on knowledge-based view, this paper first proposes a model to integrate IT design with relationships governance, then investigates and compares the technological and relational antecedents of collaborative innovation for focal firms in IT-enabled IORs, and finally explores the competitive performance impact of collaborative innovation. The research model is evaluated with data collected from 191 Chinese firms that digitally collaborate with their distributors. The findings suggest that digital platforms capability and two governance mechanisms (i.e., contractual governance and relational governance) work together to influence collaborative innovation, which in turn enables focal firms to obtain competitive performance. This study provides theoretical and practical implications for collaborative innovation literature by discovering the different impacts of IT design and governance mechanisms on collaborative innovation in the context of IT-enabled IORs.
Keywords: collaborative innovation; inter-organizational relationships; IT design; relationships governance.
Construction of distance teaching platform based on mobile communication technology
by Hongxia Li
Abstract: With the development and application of mobile communication technology, people have higher requirements for the transmission and reception of information, and this brings opportunities for distance learning. In view of this, this article has carried on the research to the long-distance teaching platform construction based on the mobile communication technology. First of all, this paper briefly introduces the application type of mobile communication technology in distance education; and then, this paper explores the framework and function of distance learning platform based on mobile communication technology, and gives the specific platform system framework and function modules of figure; finally, the main functions of the distance learning platform based on mobile communication technology are implemented and tested in this paper. The results of this paper show that the system can meet the design requirements, and can achieve distance learning and mobile learning. At the same time, the distance education institutions can transfer more learning resources to learners at a higher speed. The distance teaching platform based on mobile communication technology has a good application prospect, and the platform can exchange information with the traditional campus network to realize the data sharing.
Keywords: mobile communication technologies; distance learning platform; data sharing.
A novel replication scheme based on prediction technology in virtual P2P storage platform
by Peng Xiao, Tienan Zhang
Abstract: Recently, peer-to-peer (P2P) platforms have emerged as promising virtual storage platforms in many areas. However, most of P2P storage platforms are facing the challenging that how to maintain the data availability in such a volunteer-participating environments. In this paper, we present a novel technique which can figure out the probability of peers failure during a given period. Based on this technique, we are enabled to evaluate the failure probability of any groups of peers so as to estimate the optimal number of replicas that can achieve better tradeoffs between performance and data availability in P2P platforms. Extensive experiments in a real-world P2P platform indicate that the proposed replication scheme is effective to improving the data availability. In addition, it also exhibits better adaptive when the P2P platform is working in volunteering computing paradigm.
Keywords: peer-to-peer; data availability; quality of service; replication scheme.
Privacy-Invading Mechanisms in E-Commerce A Case Study on German Tourism Websites
by Tatiana Ermakova, Anke Hohensee, Ines Orlamunde, Benjamin Fabian
Keywords: e-commerce; privacy; web tracking; personal data; data collection.
An Efficient Adaptive Genetic Algorithm (GA) Technique to Improve the Neural Network (NN) Performance with aid of Adaptive GA Operators
by Kishor Kumar Katha, Suresh Pabboju
Abstract: The neural network (NN) performance improvement is one of the major topics. Thus an Adaptive Genetic algorithm (AGA) technique is proposed by making adaptive with respect to genetic operators like crossover and mutation. Our adaptive GA technique starts with the generation of initial population as same as the normal GA and performs the fitness calculation for each individual generated chromosome. After that, the genetic operators crossover and mutation will be performed on the best chromosomes. The AGA technique will be utilized in the NN performance improvement process. The AGA will utilize some parameters obtained from the NN by back propagation algorithm. The utilization of NN parameters by AGA will improve the NN performance. Hence, the NN performance can be improved more effectively by achieving high performance ratio than the conventional GA with NN. The technique will be implemented in the working platform of MATLAB and the results will be analysed to demonstrate the performance of the proposed Adaptive Genetic Algorithm (AGA).
Keywords: Adaptive Genetic algorithm (AGA); Genetic algorithm (GA); Back propagation algorithm (BPA); Artificial Neural Network (ANN); crossover and mutation.
A Survey on Data Stream, Big Data and Real-Time
by Eliza Helena Areias Gomes, Patricia Della Mea Plentz, Carlos Roberto De Rolt, Mario Antonio Ribeiro Dantas
Abstract: Real-time concept is being widely used by a society that seeks to speed communications, decisions and their daily activities. Even though this term is not used with the necessary conceptual precision, it makes clear the importance that time exerts on computer systems. Nowadays, the big data scenario, this concept is important and used with different meanings, which can define failure or successful of applications. This article aims to present a systematic literature review on the topics of data stream, big data and real-time. For this, we developed a protocol revision in which were determined research questions, the search term, the search source and the inclusion and exclusion criteria of articles. After an extensive study, we classify the articles selected in seven categories according to real-time concept used. Finally, we present a discussion that shows that there is not convergence on real-time concepts in the Big Data literature, authors usually adopt the most appropriate concept for their proposal.
Keywords: Real-time; Big Data; Data Stream; Stream Processing; Big Data Stream Tools.
An adaptive redundant reservation admission in virtual cloud environment
by Dongbo Liu, Yongjian Li
Abstract: In cloud platforms, resource reservation service is an effective approach to providing desirable quality of service (QoS) for user applications. However, conventional reservation service might result in lower resource utilization and higher rejection rate if it is excessively applied. In this paper, we proposed an adaptive redundant reservation strategy, which uses overlapping technique to implement reservation admission and enable resource providers dynamically determine the best redundant degree at runtime. By overlapping a new reservation with an existing one, a request whose reservation requirements can not be satisfied in a traditional way might be accepted. Also, by dynamically determining the best redundant degree, the proposed strategy can obtain optimal tradeoffs between performance and reliability for cloud platforms. Experimental results show that the proposed reservation service can bring about remarkably higher resource utilization and lower rejection rate when using redundant reservation service at the price of a slightly increasing of reservation violations.
Keywords: cloud computing; resource virtualization; quality of service; resource reservation.
Motivation, Governance, Efficacy and Contribution: A Social Practice Model of Commons-Based Peer Production.
by Rong Wang
Abstract: This study examines how individual motivation and governance structure of online collaboration affect individual contribution and efficacy in a Commons-based Peer Production (CBPP) community. Using survey data and structural equation modeling, this study demonstrates motivational factors alone cannot fully predict CBPP outcomes. How people perceive their freedom in setting their own agenda affects their confidence in producing artefacts for reuse. It also provides evidence that how individuals perceive their own ability in peer production significantly affects their relationships with the collective. Built upon a social practice view, this study highlights that efficacy at both individual and community levels should be viewed as important outcomes of cooperative human activity. This study contributes to the literature on CBPP and virtual communities by demonstrating the value of open governance and self-efficacy (128 words).
Keywords: Commons-based peer production; self-efficacy; collective efficacy; online community; collective action; governance; structural equation modeling; social practice; online collaboration.
A novel QoS negotiation model based on intelligent learning technique in clouds
by Dongbo Liu, Yongjian Li
Abstract: As more and more high-end applications have been deployed on cloud platforms, the quality-of-service (QoS) of cloud platform has become an important issue that need to be addressed. To achieve desirable QoS, an efficient negotiation model plays a critical role because cloud application often requires plenty of resource during their execution. In this paper, we propose a novel QoS negotiation model which applies intelligent learning technique to adjust the negotiation policy, in this way, QoS agreement between application and resource provider can be quickly achieved even when multiple resource requests are involved concurrently. The proposed negotiation model is implemented in an integrated QoS negotiation framework, in which negotiation agents help to make resource reservations while allocations agents are responsible for committing those reservation requests. The proposed framework is tested in a real cloud platform, and the results indicate that it can significantly improve the negotiation efficiency comparing with other negotiation methods. In addition, the experimental results also show that by using the proposed negotiation model, large-scale workflow applications can reduce their makespan by about 7%~11%.
Keywords: cloud computing; negotiation model; resource allocation; workflow.
A novel scheduling algorithm for data-intensive workflow in virtualized clouds
by Feng Li
Abstract: In cloud platforms, workflow applications have been widely used to solve the complicated problems, which often need to process a large volume of data. However, the characteristic of data-intensive for these applications are easily to result in low execution efficiency due to networking traffic or congestion. In this paper, we present a workflow scheduling algorithm which is capable of minimizing the cost of networking communication and therefore improving the execution efficiency of those workflow applications. Extensive experiments are conducted on some real-world workflows to examine the performance of the proposed algorithm, and the results show that it can significantly reduce the communication cost and improve the execution efficiency of data-intensive workflows comparing with existing algorithms.
Keywords: cloud computing; virtual machine; workflow; task scheduling.
An efficient replication scheme based on living-replicas estimation for distributed storage platforms
by Ying Hu
Abstract: In the past few years, massive storage platforms are playing critical roles in many practical distributed systems (i.e., grid or cloud). To ensure desirable data availability, replication mechanism has been widely applied in those massive storage platforms. Meanwhile, a high level of data redundancy inevitably degrades the performance of storage management and bandwidth utilization. In this paper, we propose an intelligent replication scheme which leverages failure pattern of storage nodes to estimate the actual number of living-replicas in a storage platform. In this way, the storage platform can make more accurate decisions on how many replicas should be generated for maintaining a given data availability. Extensive experiments based on real-world traces indicate that the proposed replication scheme can significantly reduce the overall data redundancy and maintain desirable data availability at the same time.
Keywords: data replication; cloud computing; distributed storage; probability model.
Stochastic Demand Side Management in Smart Grid System
by MANISH KUMAR, Cherian Samuel
Abstract: Two-way communication of smart grid gives customer involvement and allows them to see their energy consumption to make the decision in demand side management, and it also makes the energy supplier informed to manage economic dispatch based on load demand. This leads the sustainable development of the smart grid along with the reduction of operational cost and carbon emission levels. Statistical analysis of demand-side management gives us the fitness of hourly load demand with proposed probability density functions. This help in decision making to know about load consumption trend of consumers demand. We proposed Lognormal, Gamma and Weibull probability density function for estimating the load demand at Banaras Hindu University (BHU) campus. We have collected the hourly load demand data of BHU campus for a year taken from the Electricity & Water Supply Service Center, BHU. The fitness of data with theoretical probability density function has been analyzed with three goodness-of-fit tests named Kolmogorov-Smirnov, Anderson-Darling, and Cramer-von Mises test. Modern R programming language software has been used for the computational work and graphical analysis. With this analysis, we can manage optimal power flow between demand-supply and increased system reliability. This shows that the two-way communication and secured information sharing through smart grid give better control over the power distribution.
Keywords: Demand Side Management; Smart Grid; Stochastic demand; Load demand; Probability distribution; Goodness-of-fit test.
PTRE: a probabilistic two-phase replication elimination policy in large-scale distributed storage platforms
by Ning Han, Dongbo Liu
Abstract: To support large-scale data-intensive applications, massive distributed storage platform are being widely deployed in more and more IT-infrastructures. One of the most mentioned issues on distributed storage platform is how to maintain desirable data availability without too many extra costs. Therefore, data replication service plays a key role to achieve this goal. Unfortunately, many existing replication policies are designed for small-scale or centralized storage platforms, and their performance tends to be dramatically degraded when a system consists of thousands of autonomous storage nodes. In this paper, we present a novel replication policy that allows a storage platform to eliminate useless replicas and maintain sufficient data availability at the same time. Through theoretical analysis, we have proven that the costs of the proposed policy is linearly increased with the number of underlying storage nodes, which means that it can be easily applied in large-scale distributed storage platform. The experimental results indicate that the proposed replication scheme can significant improve the effective utilization of storage resources comparing with other existing policies. In addition, it exhibits a better robustness when the underlying storage platform is in presence of dramatically fluctuant workload.
Keywords: distributed storage; replication scheme; availability; probability theory.
Topology-Aware Approach for Reducing Power Consumption in Backbone Networks
by Mohammed Hussein
Abstract: According to several studies, line cards are the major source of energy savings in green networks because they contribute up to 42% of the total energy consumption of a backbone router. Since these networks are overprovisioned, during periods of low-demands shutting down network links seems like a good approach to reduce energy consumption. In this paper, we propose a novel topology-aware approach to exploit the sleep mode capabilities of links in IP networks.
We leverage the algebraic connectivity metric, adopted from spectral graph theory on IP networks in order to identify the set of links, that can be powered off by decreasing the network connectivity the least. Exhaustive searching for the optimal link shutting down is computationally infeasible. Hence, we propose several strategies that select single link for removal, based on topological and spectral metrics.
Moreover, the proposed algorithms do not require the knowledge of traffic matrix, being able to run in real-time, where this information would not be available. Results, obtained on real topologies prove that our algorithms are able to achieve performance comparable to a pioneering more complex traffic-aware approaches, called Benchmark  and Least-Flow .
Keywords: Energy efficiency; Wired networks; Graph theory.
(De)Mystifying the Information and Communication Technology Business Model Concept
by Trevor Clohessy, Thomas Acton, Lorraine Morgan
Abstract: Modern enterprises are currently experiencing volatile and rapid information and communication technology (ICT) change. A key challenge for business leaders is to ensure their organisations are ready for that change. This is particularly challenging when it comes to emerging ICT that may disrupt the management of existing enterprise information systems or business processes. The business model has been cited as an effective tool which organisations can use to prepare for ICT related change. However, there is evidence to suggest that the business model remains largely a nebulous concept to most organisations. This is compounded by the siloed nature of existing business model research. Using a content analysis research approach, this paper provides a holistic review of contemporary academic literature to ascertain and classify the various approaches to the study of ICT enabled business models. The literature examined is classified into nine specific thematic descriptors which underpin these specific business models. A comprehensive definition is also developed for ICT business models. This paper therefore extends our understanding of the business model concept and can be used to guide and coalesce future research on illuminating how organisations can operationalise effective business models in order to leverage new digital ICT.
Keywords: Business model; Information systems; Information and communication technology; content analysis; thematic descriptors.
Mobile Learning Adoption in Jordan: Technology Influencing Factors
by Mohammad Al-Nawayseh, Aladdin Baarah, Mohammad Alnabhan, Sultan Al-masaeed
Abstract: Massive progress in ICT and the emergence of mobile internet as a primary platform for information delivery has spurred the development of mobile learning. In order to utilize m-learning in Jordan, it is vital to explore the factors that impact university students adoption. This quantitative study examines factors affecting students intention to adopt m-learning using the Unified Theory of Acceptance and Use of Technology (UTAUT). The results show that students in Jordanian universities believe that m-learning performance expectancy, effort expectancy and social influence will positively affect their intension to adopt m-learning, while facilitating conditions will not.
Keywords: m-learning; adoption; technology acceptance; Jordan.
An efficient data transfer service for scientific applications in cloud environments
by Ying Hu, Changsong Liu
Abstract: Recently, more and more data-intensive scientific applications have been deployed in cloud environments. Therefore, how to improve the efficiency of data transfer becomes an important issued that needs to be addressed. In this paper, we present an efficient data transfer framework which provides an integrated platform for data transfer, data scheduling and performance monitoring. Unlike those existing studies that focus on the utilization of bandwidth resources, the proposed framework is implemented by integrating data transfer service and data scheduling service through a performance prediction service. In this way, it provides a flexible mechanism to enable a cloud system to improve the efficiency of data transfer. The implementation of the proposed framework has been deployed in a real-world cloud system, and experimental results have shown that in can significantly improve the efficiency of massive-data transfer comparing with many existing approaches.
Keywords: cloud computing; data transfer; data scheduler; performance prediction.
Hybridization of Oppositional Center based Genetic algorithms for resource allocation in cloud
by Uma Maheswari K.M., Govindarajan S.
Abstract: Cloud computing is an attractive computing model since it allows for the provision of resources on-demand. In cloud computing, resource allocation is one of the challenging problems; because when the clients want to allocate the resource to particular task while attaining minimum cost. To overcome the problem, in this work we introduce a novel technique for resource allocation in cloud computing using Oppositional Center based Genetic algorithm. For optimization, we hybridize the center based genetic algorithm with Opposition-based learning (OBL), where OBL is improving the performance of the center based genetic algorithm while optimizing the bi-objective function. The main aim is to assign the corresponding resources to each subtask within the minimum cost. The generated solution is competent to the quality of service (QoS) and enhances IaaS suppliers believability. For experimentation, we compare our proposed hybrid algorithm with GA, and CGA algorithm.
Keywords: Resource allocation; cloud computing; HCFA; Scheduling; deadline; hybridization; bi-objective.
Energy efficient-Dynamic and Self-optimized Routing In Wireless Sensor Network Based on Ant Colony Optimization.
by Arindam Debnath, Mrinal Kanti Debbarma
Abstract: A wireless sensor network (WSN) consists of low power, low cost, limited memory and small in size sensor nodes, organize them in a cooperative network and perform three basic operations - sensing data from environment, computation, and data routing. Routing in WSN mainly focuses on data dissemination, data aggregation, life time of the network and limited bandwidth constraints in order to facilitate the efficient working of the network. Due to the limited battery power, the Energy Conservation is a critical aspect to design an efficient routing protocol in WSN. This paper proposes the Energy efficient dynamic and Self- optimized routing to prolong the life time of the network, QoS and solve the stagnation problem in the network.
Keywords: Wireless Sensor Network; ACO; Forward Ant (FA); Backward Ant (BA); Local Edge Selection.
WBMR: A new Communication Scheme for Multicast Routing in MANETs
by Arappali Nedumaran, V. Jeyalakshmi
Abstract: There is a great demand for multicast route deployment and time varying link strategies which makes routing difficult in ad-hoc networks. Thus finding the optimal routes with multicast behavior in Mobile Ad-Hoc Networks (MANETs) is a critical issue. The deployed route should fulfil the necessary requirements of MANET, like power utilization, efficient utilization of bandwidth, loop free communication, link stability and minimized usage of control overheads. Thus in research, the proposed Weight Based Multicast Routing (WBMR) protocol addresses the critical issues like loop free communication and link stability, which simultaneously yields the optimum routes and reduced energy utilization of the nodes in MANETs. This proposition uses the weight based routing approach which is based on the distance and (Signal to Noise Ratio) SNR of the demanding links. This WBMR protocol minimize the number of nodes participated in the communication in association with link stability and thus minimize the unnecessary utilization of bandwidth and energy. The simulated results show that the implemented approach outperforms well when compared with the existing approaches in multicast routing schemes.
Keywords: MANET; Multicast Routing; SNR; Distance; Loop free; Energy Utilization.
A QoS-aware resource allocation framework in virtualized cloud environments
by Yuan Tian
Abstract: In cloud platforms, resource allocation service plays an important role for running user applications efficiently. However, current allocation mechanism in many cloud platforms only provides best-effort service for users jobs, which means that users quality-of-service (QoS) requirements can not be well guaranteed. In this paper, we present a novel QoS-aware resource allocation framework, which applies feedback control technique to achieve the goal of fair resource allocation between multiple virtual machine (VM) instances. Theoretical analysis of the proposed control model has proven that it can meet the feasibility and stability requirements. Experimental results conducted on a real-world cloud platform show that the proposed resource allocation framework can significantly improve the effective resource utilization as well as the overall task execution efficiency. In addition, the proposed framework also shows better robustness when the cloud platform is in presence of highly dynamic workload.
Keywords: cloud computing; virtual machine; resource allocation; quality of service.
IDENTIFICATION AND ERADICATION OF MALICIOUS NODE IN MANET
by Gayathri VM, Nedunchelian R
Abstract: Mobile ad-hoc network plays a vital base for the future networking ideologies. A MANET is a part of wireless network which forms a topology based on their communication range or distance. Each node in the network is responsible for efficient communication. Each node acts as router and passes data packets from source to destination. Nodes may be either in static or mobile in nature. If any malicious node enters into the network it might result in loss of data packets. However, it is possible to identify the malicious nodes based on send and receive packet information and change the route from source node to destination node. The malicious path can be identified by calculating the packet drop count.
Keywords: MANET;Intruder;Packet delivery ratio;Mobility;WSN;VANET;DTN.
A Novel Approach for Intrusion Detection in Mobile Ad-hoc Networks
by Bhushan Chaudhari, Rajesh Prasad
Abstract: Mobile Ad-hoc Network (MANET) consists of various nodes and they interact with each other cooperatively. However, the cooperative nature of MANET provides a gateway for intruders to interrupt the communication. Two types of approaches have been proposed for the IDS in the literature. The first approach has been used for the improvement in the conventional models and the second approach based on the unconventional models. Our focus is on the unconventional methods since they perform better in the diversified environment. A number of unconventional methods viz. Watchdog, EAACK etc have been discussed in the literature. However, intrusion detection model based on Particle Swarm Optimization (PSO) for distributed and advanced attacks have not been discussed yet. In this paper, we proposed a novel approach based on PSO for the IDS in MANET. The proposed model is compared with existing models like Watchdog and EAACK. Comprehensive objective function in the evaluation of node trustworthiness is a key point of this model.
Keywords: Mobile Ad-Hoc Network; Intrusion Detection System; Particle Swarm Optimization; Watchdog; EAACK.
Towards Geographical Analysis of the Autonomous System Network
by Uri Yacobi-Keller, Evgeny Savin, Benjamin Fabian, Tatiana Ermakova
Abstract: The Internet is an important global critical infrastructure. Yet, it has remained unclear how it is organized in different regions and areas of political influence. This explorative study analyses geographic aspects of the Autonomous System networks in different countries. By using Internet geolocation information for locating autonomous systems, we demonstrate the feasibility of discovering physical regions, rather than purely topological clusters, in a graph representing the backbone network of autonomous systems. We further explore the characteristics of these central regions across different countries. We identify and discuss a general pattern in the surveyed countries, but also some important exceptions. Our study can serve as a starting point for investigating potential geographical and political points of control.
Keywords: Internet Governance; Autonomous Systems; Geography; Geolocation.
Special Issue on: Swarm and Evolutionary Computational Approaches Recent Advances in Networking and Internet of Things (IoT)
A Lightweight Mutual Authentication Approach for RFID Tags in IoT Devices
by Brij Gupta
Abstract: In this paper, we present an approach for mutual authentication between server and RFID tags using hash and bitwise computations. The use of RFID technology is changing frequently these days, and their use is widespread. Due to the persistent development of Radio Frequency Identification (RFID), substantial amount of attention has been drawn towards the security issues in RFID from researchers and industries. Mutual authentication between server and the RFID tags is one of the most popular mechanisms to protect these systems from attacks, providing confidentiality, integrity and authentication. But security and privacy issues are also increasing with time as it low cost and have limited resources we need to minimize the computations and storage cost of a protocol too. Our protocol is simple and also ensures the security against various attacks. The security and performance analysis also verifies the strength of our protocol.
Keywords: Authentication, Forward secrecy, Anonymity, Tracking, Spoofing, Eavesdropping
Parallel AES algorithm for performance improvement in data analytics security for IoT
by Manikandan N, Srinivasan Subha
Abstract: In emerging computing environment like Internet of Things (IoT) or Smart device networking, many constraint based devices are connected with Internet. The device automatically interacts with each other through the connected network and gives us new experience. In order to effectively utilize the features of IoT, it is absolutely essential to ensure the security of connected end nodes. If one of the node security is compromised, the entire process will suffer seriously.. However, implementing sufficient cryptographic functions on the device is very difficult due to the limitation of resources. This paper proposes a method of injecting the high performance security algorithm in data analytics done with IOT based devices. Parallel algorithms will improve the efficiency of security mechanism in data analysis with parallel computing devices. AES algorithm is a symmetric encryption algorithm works efficiently for hardware and software. Through parallel processing of AES algorithm, Data analytics in IoT based systems performance can be improved. This method is tested with varieties of Intel based multi core processing architecture and considerable performance improvement is achieved.
Keywords: IoT security; parallel algorithm; AES algorithm; Data analytics security; IoT Performance.
Particle Swarm Optimization based DWT for symbol detection in
by Asma Bouhlel, Anis SAKLY, Mohamed Nejib Mansouri
Abstract: This paper proposes a new detection algorithm called Particular Swarm Optimization (PSO) based Discrete Wavelet Transform (DWT) for Multiple-Input-Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) system. In all previous studies, PSO detection algorithm and Discrete Wavelet Transform were separately proposed for MIMO-OFDM systems. Motivated by the performances enhancement achieved by these techniques, PSO is combined to DWT transform in this work for symbol detection in MIMO-OFDM system. Simulation results show that the proposed PSO based DWT MIMO-OFDM system boosts the performances of Zeros Forcing (ZF), Minimum Mean Square Error (MMSE), and even PSO based FFT MIMO-OFDM equalizer. The proposed detector presents near optimal performances in terms of Bit Error Rate (BER) and a significant computational complexity reduction for different constellation diagram and number of transmitting antennas compared to Maximum Likelihood (ML) detector.
Keywords: Discrete Wavelet Transform; Particular Swarm Optimization; Maximum Likelihood; Multiple -Input-Multiple-Output Orthogonal Frequency Division Multiplexing.
Optimal Cluster Head Selection Framework to Support Energy Aware Routing Protocols of Wireless Sensor Network
by Achyut Shankar, N. Jaisankar
Abstract: Data transfer to the base station from the sensor node through the choice of an optimal cluster head is a huge challenge posed for the routing protocol, in the case of the wireless sensor network. An energy proficient clustering scheme relying on artificial bee colony algorithm and fractional artificial bee colony algorithm tends to maximize the network energy and lifetime of nodes through the selection of an optimal cluster head. However, the growing complexity of the network architecture requires substantial improvement. This paper develops a weighing model as a cost function to represent the optimal cluster head selection problem. Further, the traditional ABC is enhanced by adopting a novel adaptive concept called dynamic scout bee, and hence ABC-DS algorithm is derived in this paper. According to the concept of ABC-DS, multiplicating the scout bee generation enhances the number of alive nodes and the energy of cluster head. Comparative study between the performance of the proposed ABC-DS routing mechanism against that of ABC and FABC-based routing is conducted. The simulation results show that the proposed scheme increases the number of alive nodes with 25% of maximum normalized network energy than the existing protocols.
Keywords: Wireless Sensor Networks; Cluster Head Selection; Network Lifetime; Artificial bee colony.
Special Issue on: I-SMAC 2017 IoT Based Next Generation Systems for Medical Internet Applications
Complexity Estimation by Using Multiparadigm Approach: A Proposed Metrics and Algorithms
by Neelamadhab Padhy, Suresh Chandra Satapathy, R.P. Singh
Abstract: The factors upsetting directness of a software code were calculated manually using traditional approach which is not suitable in these days. There are numerous software tools are available in the market but they are not reliable due to vast number of metrics are available and each and every metrics are not specific definitions. This paper investigated factors which are affecting for understanding the procedural and object oriented code and found that software metrics can be calculated by using the Web-Engineering technology especially Multi-paradigm language. The most important parts of this paper are propped algorithms for estimating an object oriented metrics. The planned metrics were empirically authenticated in diverse paradigms. The exigent task of this paper is all about the evaluation strategy of an object oriented metrics by using Multi-paradigm language (Java Script).The proposed model is developed to analyze the CK metric suite. This model extracts the number of classes available in the Java Script programs. Basically this model works in two different phases. In first phase the parser is able to find and generate the full abstract syntax tree and second stage the identification of the classes and generated the metrics itself.
Keywords: Code quality; Meaning software complexity;Complexity Measurement; Multiparadigm ;Proposed Metrics and Algorithms for OO.
Intelligent decision making service framework based on analytic hierarchy process in cloud environment
by Sivaraman Eswaran, Manickachezian R
Abstract: Outsourcing corporate procedures to a cloud domain is seen among the arrangements helping small and medium-sized corporate to rise in business sector and improve their additional worth. When deciding to outsource some portion of its corporate procedure to the cloud, small and medium-sized corporate ought to examine a few variables that define its particular connection. Given different variables on which depends the corporate process subcontracting to the cloud environment, a venture clearly needs a basic leadership technique. We define an endeavor setting that contains distinctive elements that help in outsourcing choice to the cloud. The manuscript demonstrates how corporate incentive model of venture additionally improves the outsourcing basic leadership by considering the corporate arrangements and vision of the undertaking. Finally, it proposes an outsourcing choice strategy that depends on expository order procedure to choose whether or not to outsource a corporate procedure to the cloud and through which administration sort.
Keywords: corporate; small and medium-sized corporate; corporate process subcontracting; corporate incentive model (CIM); information and communications technology (ICT).
FUTURE ALGORITHM FOR OPTIMIZED PATH SELECTION AND DETECTION IN MANET
by Ramesh Palanisamy, Mathivanan V
Abstract: The beginning of wireless communication gives birth to cognitive radio mobile ad hoc networks (CRAHNs). Routing is the main factor in both wired and wireless networks. Three major types of routing can be performed in CRAHNs such as proactive, reactive and hybrid. This research work aims in design and development of a hybrid protocol named efficient zone based routing protocol shortly termed as EZBRP, SACBRP and BIABRP. NS2 simulation tool is used to examine the performance of the proposed protocols. Communicating systems use well-defined formats (protocol) for exchanging various messages. Efficient Zone Based Routing Protocol (Ezbrp),Spectrum Aware Cluster Based Routing Protocol (Sacbrp),Bee Inspired Agent Based Routing Protocol (Biabrp).This Research on optimized path selection and detection in manet and a considerable research effort is still required for secured communication.
Keywords: Cognitive; Protocol; CRAHN; EZBRP; SACBRP and BIABRP; Ad Hoc; MANET.
Controlling Industrial Parameters Through Server Using Li-Fi & Wi-Fi Communication Protocols
by Surendar Aravindhan, Puligadda Bhanu Subrahmanyeswara Rao
Abstract: In the present day scenario industrial automation is the most prominent and very common phenomena. Normally to establish communication among different modules, in industrial applications CAN (controlled area network) protocol is very popular. As the number of devices connected to CAN bus increases, response time also increases for devices connected to CAN, which may lead to catastrophic effects in the system. As CAN deals with electrical signals it may generate EMI (electromagnetic interference) in signal sensitive areas. To avoid EMI and to reduce response time due to CAN bus protocols, other alternatives are to be thought of. So, to overcome the limitations and to resolve the problems due to CAN bus in industrial controlling a novel idea is proposed by the authors for controlling and monitoring the remote plant using Li-Fi. Remote plant is a signal sensitive area, where first a communication link based on Li-Fi is developed to monitor various modules of the plant and then the necessary control signals are sent through the Wi-Fi protocol to the plant to control it. This novel idea provides the unique features of high speed data transfer with reduced EMI effects greatly with higher speed of response.
Keywords: Industrial automation; CAN (controlled area network); EMI (electromagnetic interference); Li-Fi (Light fidelity); Wi-Fi module.
A Comparative Study of various existing Malware Analysis Methods
by Shilpa Mahajan
Abstract: With the advancement of technology todays world is a digital world where digital technology is generating new world of possibilites and opportunities and we are abandonded with digital data over the network that needs to be exchanged with many organizations, devices and users. This data needs to be a secure data and malware is one type of threat to this data.There are many forms of malware that can damage this sensitive data. This paper includes various malware detection techniques to detect various known and unkown binaries and presents a detailed analysis of current methods of malware detection and a malware analyzer tools.
Keywords: Malware; Analysis; Static; Dynamic;Hybrid.
Survey on Testing Technique for Modern Web Application- Rookies vantage point
by Vijaya Bharathi Manjeti, Koteswara Rao K.
Abstract: Ajax build 2.0 web applications depend in light of state full unique client and server correspondence and client side control of the DOM tree, which makes not the same as standard web applications. Provoking to more slip-ups and harder to set. Another methodology for this AJAX named ATUSA based web applications has been perceived for such accuses that can occur in any state and for making the test suite covering the ways. This approach called as ATUSA, realized by using a gadget which offers invariant checking of portions, module instrument. We portray this framework in three phases with six segments and furthermore accuse revealing limits, versatility, manual effort and level of motorization testing. This paper mainly concentrates on rookies vantage point of testing modern web application based on so far accomplished potential research done by software practitioners and experts.
Keywords: Invariants; Automatic Testing; DOM; AJAX.
An Energy Efficient and Secure Data Forwarding Scheme for Wireless Body Sensor Network
by DINESH KUMAR A, SMYS S
Abstract: Monitoring human bodies and collecting physiological information are the major healthcare applications for Wireless Body Area Networks (WBANs). Due to the limited energy resource of body sensors, their energy depletions will cause severe network performance degradation such as latency and energy efficiency. To solve this problem existing system introduced an Energy-efficient Data Forwarding Strategy (EDFS) which is used to balance sensor energy consumption and improve network lifetime and collaborative operations of heterogeneous WBANs. Additionally Compressed Sensing (CS) is performed for reducing the data size to be transmitted. However the existing system only considered the energy function for optimal relay sensor node selection, does not considered the delay and hop count of node. Hence in this system, the topsis based Artificial Bee Colony Algorithm (Topsis based ABC) is proposed to select the optimal path selection for data transmission. In this approach topsis method is used for selecting the best fitness value. The objective function of this system includes minimizing path delay, maximizing the energy and minimizing hop count. The ABC algorithm is selecting the best path by using this fitness value. To reduce the network congestion CS is performed. The compressed data are sending to sink. Then hybrid robust support vector machines for regression are used for reconstruction at sink. The reconstructed data are sending to system via gateway. Especially access to patient-related data must be strictly limited only to authorized users; otherwise, the patients privacy could be abused. To solve this problem the proposed system introduced hybrid RSA and Diffie Hellman algorithm. By using this algorithm data in a system are encrypted and it is send to hospital server. To get an original data decryption is performed at server side. The proposed methodology is implemented by using NS-2 simulator. The experimental results show that the proposed system achieves better performance compared with existing system in terms of end to end delay, packet delivery ratio and throughput.
Keywords: Compressed sensing; ABC algorithm; objective function; data reconstruction; optimal path selection and sink.
Improving the performance of MANETs to suit for IoT based applications
by Mamatha Balachandra, Prema K V
Abstract: Computation of multiple node disjoint paths is very much essential for Mobile Ad hoc Networks due to frequent topological changes. In the case of original AODV, since at a time only one path is identified, due to link break or node failure the current path becomes invalid, so immediate route discovery has to take place. In the case of original AOMDV, the path/paths that are existing in the routing table are not node disjoint. i.e., whenever there is link break or node failure in the network, the current path becomes invalid. Existing on-demand routing protocols doesnt provide efficient paths. In this work, route discovery of the original single path AODV protocol is altered by using the path accumulation feature of DSR to compute more than one path during route discovery. Among the multiple paths obtained at the destination, only node disjoint paths can be selected using the path matrix method. The modified multipath AODV i.e., Multipath Quality of Service Aware Routing Protocol (MQARP) is compared with the original AOMDV. In the context of IoT, MANETs could represent scenarios such as soldiers in military applications, people using mobile phones, disaster recovery operations etc. QoS plays a very The proposed MQARP gives better performance in terms of the QoS parameters like end-to-end delay, PDR and control overhead.
Keywords: AODV; DSR; AOMDV; QoS; Multipath; IoT; Route discovery.
Special Issue on: WHICEB 2016 E-business
Study on core essential elements for O2O business model with value net theory
by Jiangping Wan, YaHui Zhu, Qiaowen Jiang
Abstract: The O2O business model concept was given based on literature review. The O2O business model framework was established and the most basic 7 major elements were identified in our research with value net theory as follow: customer, telecom operator, content provider, service provider, software provider, third-party payment platform and offline business entity. Then, we identified 8 secondary elements and 22 three-level elements of O2O business model with Delphi, and the O2O business model core essential elements evaluation model was also established. We analyzed the model systematically and figured out top 10 core elements with analytic network process as follow: network speed and stability, mining the customer subject requirements, insight to customer demand, control the trading risk, the core technology research and development, the life service payment platform, after payment platform, financial services platform development, outburst requirements fulfillment and maintenance of direct correlation among enterprises. The top 10 elements mainly concentrated in 4 dimensions as follow: customer, telecom operators, third-party payment platform, and software providers. We hope that the research can provide enlightenment to O2O business model essence and insight to O2O future trends.
Keywords: O2O business model; core elements; value net theory; Delphi; analytic network process.
Driving Factors of Digital Strategic Actions in Competitive Dynamics
by LeWei Hu, Jing Zhao, Jiao Huang, Yajing Li
Abstract: Based on the competitive dynamics theory and from the exploitation/exploration perspective, this study explored the impetus and differences in incremental and radical digital strategic actions (DSAs) using 250 cases. We found that the quantity and diversity of partners were the core factors for launching successful incremental DSAs, and partnership strength was the core condition to start successful radical DSAs. We also found that digital assets depth and breadth were the necessary prerequisites to initiate the two types of DSAs. This study aimed to help managers formulate and initiate competitive actions more effectively in a digital environment.
Keywords: digital strategic actions; digital assets; partnership; competitive dynamics.
Special Issue on: Future Generation Wireless Networks
Reduction of Overhead in Routing Protocols for MANET Using Fuzzy Set Based Decision Making
by Preetha K G, A. Unnikrishnan
Abstract: It is well known that dynamic topology, mobility of nodes, infrastructure less property and absence of central coordinator, make the behaviour of Mobile Ad hoc Network (MANET) uncertain. Routing is the major step in the operation of MANET and the establishment of route from source to destination thus becomes crucial. Routing decision is distributed among the nodes in the network and the reliable and effective routing predominantly depends on proper establishment of route from source to destination. Route establishment depends largely on control packets and those packets induce more overhead in the network, which in turn degrades the performance of the network. The present work proposes a novel method to reduce the control overhead by predicting the quality of the neighbouring nodes that sustain more, using a fuzzy set decision approach. The flooding of control packets is based on a fuzzy decision taken on success rate of each link in the previous trials and residual energy of the neighbouring nodes. Simulation study reveals that this approach significantly reduces the control overhead in the network and improves the overall performance.
Keywords: MANET; Fuzzy Se; Knowledge Base; Decision making.
Performance measure of routing protocol with angular coordinates and distinctive transmissions in wireless networks
by Mani Vanitha, T.R. Ganesh Babu
Abstract: This work focuses on two geographical routing protocols for proficient forwarding with minimal overhead. The first protocol namely proficient geographical routing with angular coordinates (PGRA). The protocol PGRA attains efficiency in obtaining its geographical coordinates of destination without the aid of Global Positioning System (GPS). This is done by obtaining the angular coordinates. In addition, the protocol monitors the desired throughput with exponentially weighted moving average (EWMA) method to determine whether to continue forwarding or interrupt current transmission. In the second work proficient geographical routing with angular and vector coordinates (PGRA-V) obtain the information of forwarding nodes by meticulously increasing the communication radius. The protocol limits the transmission at the advance node and refrains from flooding control packets. Performance comparison of both the proposed protocol has been done with similar geographic routing protocol with zone based structure Energy Efficient Geographic DSR over AODV (EEGDOA).
Keywords: PGRA; PGRA-V; geographical unicasting; EWMA.
Scalability Assurance Process in Replication and Migration Using Cloud Simulator
by Deivendran P., Naganathan ER
Abstract: In service-oriented computing, service customers call up services deployed by service providers, and service providers are responsible to deal with the excellence of their services including scalability, accessibility and performance. In particularly, scalability is tough to get, mainly due to the unidentified nature of service customers and changeable volumes of service invocations. Services with underprivileged scalability would be defeated the consumer basis, resultant in small revenues. Predictable approach to scalability of network, database, and scattered computing are hardware-oriented solutions. In this paper, we present software-oriented approaches to guarantee elevated scalability of services in cloud computing. We first identify scalability in service-oriented computing, present suitable foundation of services scalability. Then, we present two efficient scalability assure scheme; service replication and migration. The future schemes are well-known from predictable scalability schemes in three ways; adapted for service-oriented computing, software solutions quite than hardware solutions, and being implementable with in progress SOA and languages. To give you an idea about the applicability of planned schemes, we demonstrate a result of implementing the scheme and experiments with them. Through means of the methods, services scalability can be to the highest degree improved enthusiastically by using software solutions. Growth of large network infrastructures have led to several systems that design large scale distributed systems supporting efficient, secure, and available services
Keywords: Cloud computing; scalability; migration; service; networks; and distributed performance.
Efficient Network Coding Based Data Transfer Framework for Multihop Wireless Communication
by Nyan Lin, Yasuo TAN, Yuto LIM
Abstract: With the growing demands of wireless applications and mobile data connections, wireless communication is expected to provide the ever-increasing demand for higher data rate and efficient data communication. Energy is also one of the hot issues needed to be considered for future wireless networks. In this paper, an Efficient network coding based data transfer (E-neco) framework is developed to achieve more energy-saving and bandwidth-efficient data communication for data transmission, data collection and data sharing services. For these data transfer applications, we propose new network coding based transmission schemes and medium access control protocols. Topology and network coding techniques are utilised in the framework. This is a conceptual framework developed for future generation wireless communication such as multihop communication, massive machine communication, device-to-device communication and new techniques can be added to support future demanding services. Simulation results reveal an improvement in terms of throughput, latency, fairness, energy consumption and network lifetime.
Keywords: Multihop wireless communication; Network coding; Medium access control protocol; Data transfer framework; Energy efficient protocols; Wireless network topology; Future wireless networks.
A POWER AWARE MECHANISM FOR ENERGY EFFICIENT ROUTING IN MANET
by Chandra Sekar P., Mangalam H.
Abstract: In this paper, Mobile Ad hoc Network (MANET) is used to refer a wireless network wherein there is no definite architecture and required configuration is done by itself. Multiple protocols are suggested to reducing the overall transmission power in MANET routing. Several multicasting routing protocols are available and two of them are Power aware Dual Tree based Multicast Routing Protocol (PDTMRP) and Load balancing and Power aware Multicast Routing in MANET (LPMR). Here, a Power Aware Mechanism for Energy efficient Routing (PAMER) for MANET is designed to improve route stability as well as to obtain load balance data transmission by taking into account the Energy Reduction Rate (ERR) as well as Residual Energy (RE). A suitable Band Width (BW) assessment is integrated to respond to network traffic as well as explore a QoS aware strategy into route discovery for appropriate traffic Management. Thus, the improved system can monitor overhead, lessen the number of route reconstruction as well as improve the life span of network.
Keywords: Mobile Ad hoc Network (MANET); Traffic Management; QoS Aware Strategy; Residual Energy.
A NOVEL ROUTING PROTOCOL FOR RELAY NODE BASED ENERGY CONSUMPTION IN MANET
by Perumal Sivanesan
Abstract: In MANET data replication play major role for energy conservation. Redundant data transmission makes network traffic heavier and causes unnecessary energy utilization. This paper addresses the problems due to the network traffic and unnecessary energy utilization. It proposes the Relay node Based Routing protocol (RBP) to minimize the data replication and energy consumption. The relay node is implemented to collect the data from neighbors based on the stochastic process. The data is predicted by time series forecast then an error value is found. The autocorrelation function is used to compare the current variable with the predefined one (calculated error bound). If the output error value greater than predefined error value then the received data is sent to the sink as it is; otherwise the received data is discarded and the index only transmitted to the sink.
Keywords: Data replication;Energy consumption; Relay node selection.
PRIVACY ANDSECURITY ISSUES IN CLOUD COMPUTING USING IDYLLIC APPROACH
by Santhosh Kumar P.
Abstract: Provides pay service model as per user need and requirement. The cloud provides the collection of virtual machine which have both computational and storage facility. The important aspect of cloud computing is to present effective process to hyper distributed resources. Now days, Cloud system is developing and facing many challenges, two of them is scheduling process and other main challenge is a security issue. In existing approaches did not concentrate on both security and scheduling issues in the cloud computing. Scheduling refers to the scheduler adapts its scheduling strategy, according to the changing to a set of morals to control the order of work to be implemented by a computer system. In this research paper, we have implemented a scheduling algorithm of Collocate FCFS (First Come First Server) of Supremacy elements. Here, we improve the system efficiency by using FCFS in a parallel manner. Security and privacy protection is a complex matter in the development and adoption of cloud computing. To address this security issue, we have introduced a novel concept of Crisscross AES (Advance Encryption Standard). In existing method, they have implemented the security remedies using IAES (Improved Advance Encryption Standard), thus produce fewer security measures. But in this approach, Crisscross AES has implemented by increasing the security to the cloud through the grid manner. Aggregate of this proposed work is to enhance the system efficiency as well as the security by using the both Crisscross AES and Collocate FCFS of Supremacy elements.
Keywords: Virtual machine; Collocate; Computational; Crisscross; Efficiency.
Estimation of Complexity by Using an Object Oriented Metrics Approach and Its Proposed Algorithm and Model
by Neelamadhab Padhy, Suresh Satapathy, Singh RP
Abstract: The high pace emergence of software applications and associated technologies have enabled us an efficient and luxurious. This research paper focus the procedure of investigating the different object oriented metrics by taking an example and finally evaluate complexities, statistical measurements. A proposed model, flowchart and algorithm is used for measuring the metrics in the software project. Comparison done between the programming languages like C++ and Python and conclude that Python is better than C++.
Keywords: Object Oriented Metrics; CK Metrics Suite Object Oriented Programming Examples; Proposed Algorithm and Models.
A Novel Boot Strapping Algorithm for Text Extraction in a Self-Organizing Neural Network Model
by Xiaohong Li, Maolin Li
Abstract: With rapid growth in internet and its associated communication protocols, need for printed documents to be carried over from one place to another has been reduced to minimize the cost and time. Research contributions in the past have paved the way for implementation of smart and intelligent algorithms to further minimize manual intervention in processing of documents. One such area is the automation of text extraction from documents with increased accuracy and least number of false detections. A wide range of algorithms and methodologies have been reported in the past towards efficient extraction of text from documents which may be online or offline. This research paper proposes an efficient extraction algorithm of text from given set of documents which may or may not be graphic through utilization of a hybrid SOM ANN algorithm. The experimentation has been done over a wide variety of inputs and convergence of error in extraction is found to be minimum when compared to other conventional extractors.
Keywords: Extraction algorithms; intelligent extractors; neural networks; SOM; bootstrapping.
Error Free Backbone Tree Construction to Expand the Longevity of Wireless
by Vimal Kumar Stephen K., Mathivanan V
Abstract: Wireless Sensor Networks (WSN) raises number of the challenges with regard to scalability and energy efficacy. Implemented of Huffman approaches One of the key variable length in the wireless sensor network is prolonging network lifetimes. To improve the lifetime of the sensor, static and movable mobile sinks are deployed. Movable sinks are used to receive sensed data from the sensor where it is located. Assigning prime number as the sensor node identity can be easily guessed by the intruder. Reusing the same identity in the cluster leads to compromising of nodes. The energy is retained when computation is reduced in cluster head thereby increases the life time of the particular cluster. Variable length gives variable length identity and avoids reusing of same identity hence it avoid network attacks such as random number length of nodes are not possible (No sensors are allowed inside the network without the knowledge of Cluster head).Increasing transmission range future will consume more battery power.
Keywords: Component; Formatting; Style; Styling; Insert.
Special Issue on: Exploring Emerging Verticals in the Future of Wireless Technology
A FULL-FEATURED EFFICIENT CLUSTERING MECHANISM FOR HIGHLY IMPROVING QOS IN MANETs
by Gatete Marcel, A. Kovalan
Abstract: Due to the dynamicity of MANETs topology and its infrastructure less nature, various problems arise from those inherent properties which are often related to control traffic-related issue. Problems faced with MANETs are the energy constraints, broadcasting, and high mobility and also MANET faces various challenges during the path discovery, route selection, packet scheduling and packet transmission processes. The last and very dangerous negative issue often faced in MANET is related to malicious nodes detection. To find an efficient solution to all those problems, in this paper, we propose a robust algorithm; Full-Featured Secure Routing Clustering Algorithm with Energy-Aware and Scheduling capabilities for highly increasing QoS in MANET (FSR-CAES), an efficient clustering technique which is a combination of numerous algorithms, each one containing one of the previously mentioned problems. The simulation results are provided with the NS-2 simulator varying the number of nodes and the evaluating parameters namely the routing overhead, packet delivery ratio, normalized routing load, and the average end-to-end delay while comparing the performance of our proposed scheme with NCPR (Neighbor Coverage-based Probabilistic Rebroadcast (NCPR), a routing protocol specialized in providing high QoS in MANETs as it is efficient in reducing the routing overhead in the network. The outcomes prove that our proposed scheme outperforms NCPR for all the studied scenarios for small, medium, and large MANETs.
Keywords: MANET; QoS; Energy-Aware; Security; Mobility; Scheduling; and Clustering.
ASD: EMOTIONS AND BEHAVIORAL BASED INTERVENTIONS THROUGH SOCIAL SENSOR NETWORKS
by Faustin Uwizeyimana, Kovalan A
Abstract: In India, nowadays one per 88 children is born with Autism Spectrum disorder (ASD) contrary to a ratio of one per 110 children few years back. The Autism Spectrum Disorder (ASD) and bipolar disorders are prevalent and costly neuro developmental disorder. Individuals with ASD often have deficits in social communication skills as well as adaptive behavior skills related to daily activities. In this paper, we propose a social sensor network for individuals with ASD to offer medical promotions as intervention and first aid. The Autism spectrum disorder is naturally self-injurious behavior, pica, smearing, and they are in highly surveillance environment. They should be in care and medical surveillances. We explored the feasibility of detecting engagement level, emotional states, and mental workload of ASD Childs during abnormal period and behavior model shared in social networks where medical advisories are connected in that group . We are monitoring enjoyment, frustration, boredom, and stress by using body-worn sensors and video streaming analysis as a classification models. This sensor collects the information from the human body and transmit it to their smart phones then to the external server. The various emotion levels are classified by SVM classifier. We introduce an algorithm named as spectrum Clustering Algorithm (SCA) which clusters people based on activities of the child. Communication is provided between the clusters of people by using context Recommendation Algorithm in our process. We use PRA (Prerogative Response Algorithm) algorithm for load balancing on server while processing the requests. Our processes are simulated using Omnet++ simulator and provide effective results in terms of Overhead, Growth rate, and Efficiency.
Keywords: Social Networks; Sensor Networks; Load balancing; Zone routing protocol; Clustering; ASD.
MALICIOUS NODE IDENTIFICATION ROUTING AND PROTECTION MECHANISM FOR VANET AGAINST VARIOUS ATTACKS
by Zaid Abdulkader, Azizol Abdullah
Abstract: VANET (Vehicular Ad-hoc Network) is a promising approach that provides safety measures and other application to the drivers on the vehicles. The focus of VANETs is to fulfill users requirements on road side area which increases the safe and comfortable journey for users. It provides good communication like MANET (Mobile Ad-hoc Network) when there is no intruders exist in the network. In VANET, communication depends on road safety such as emergency situation, vehicles tracking, messages monitoring and tracking of vehicles. But many attackers like black hole attack, Wormhole attack and Sybil attack are more vulnerable to VANET. In order to provide efficient communication, we provide a Malicious Node Identification Routing mechanism which gives the valid route between two vehicles. To avoid several attacks, we introduce a Protection Mechanism that includes key management for preventing our network. Our proposed system provides efficient communication on VANET that focus on Throughput, End-to-End delay, Packet delivery ratio, Detection rate and Misdetection rate.
Keywords: Black hole attack; Sybil attack; Wormhole attack; VANET; AODV Routing; Elliptical Curve Cryptography.
Relay Node Selection with Energy Efficient Routing using Hidden Markov Model in Wireless Sensor Networks
by J. Martin Sahayaraj, J.M. Ganaseakar
Abstract: Wireless sensor based routing is a challenging issue in the context of convergecast routing. In order to counter these issues the relay nodes share the burden of forwarding in multi-hop routing. In this research to counter the effect Energy efficient Relay Node Routing (ERNR) algorithm is proposed. ERNR relay nodes are found among the group of member nodes based on the residual energy of the node using voronoi cells. The selected relay nodes with two hop neighbors forms virtual subsets of cluster. The cluster head is then used to allocate the TDMA time slots to its neighbors based on the Hidden Markov prediction model. The proposed technique is evaluated with existing relay node based routing schemes and the performance of the ERNR algorithm yields significant improvements while considering energy related metrics.
Keywords: WSN; Routing; Markov Model; Relay node; Energy consumption.
Network lifetime estimation of wireless sensor networks using communication protocols with non parametric models
by Govindarajan SARAVANAN, M.J.S. Rangachar
Abstract: In this research the focus lies on estimating the network lifetime in wireless sensor networks with the aid of directional antenna. Two protocols are being proposed the (NLKM) Network Lifetime with Kaplan Meier and (NLNPM) Network Lifetime with Non Parametric model. In NLKM estimates where a control packet calculates all the sensor residual energy and decides whether to transmit or not based the residual energy. The directional antenna is used to avoid forwarding of packets in all direction and focus on the direction towards the destination and increasing its communication range based on dead nodes. In the second protocol NLNPM is similar to the operation where the residual energy is calculated with two thresholds dead and almost dead. This NLNPM based protocol with censoring there by overcomes the limitation of empirical distribution of Kaplan Meier analysis. Both protocols were simulated in ns2 simulator and compared for network lifetime.
Keywords: Wireless sensor nodes;Network lifetime;Non parametric models.
COMBINED VIBRATION AND RF HARVESTER (CVRH) TECHNIQUE FOR ENERGY MANAGEMENT IN SENSOR DEVICE
by Padmavathy C., Jayashree L. S
Abstract: The main objective of this research work is to increase the energy efficiency in the wireless sensor network through the energy harvesting techniques. Proposed the Combined Vibration and RF Harvester (CVRH) technique can increase the energy efficiency and reduce the energy consumption. In WSN, sensor node has high energy consumption due to the process of sensing and transferring. To reduce the energy consumption and to refill the battery this proposed technique has been used. From the physical environmental condition, vibration and RF energy will be collected from their respective ambient source. Vibration and RF energy are in the form of an electromagnetic wave and that will be converted into DC by using the bridge wave rectifier. And that DC current will be the supply of the battery of sensor node. During the sensing process, battery will be utilized by the sensor node and in the transmission process, the battery will be charged from the energy harvester. In experimental results, results have been analyzed by using the parameters such as energy consumption, energy efficiency, and average power and Drop rate.
Keywords: Energy harvesting; vibration energy; RF energy; WSN; Energy efficiency; Power consumption.
DTCF: Deadline Task Consolidation First for energy minimization in cloud data centers
by Sanjeevi P, Viswanathan P
Abstract: The consumption of energy is a vital issue in the cloud, when
more precisely administering a large-scale data center. The cloud data centers
accommodating more hosts consume an extent of energy for computation which
increases the consumption of energy. To handle this issue, we propose a heuristics
energy-efficient workload consolidation with deadline constraint to optimize
energy in cloud data centers. The Deadline Task Consolidation First algorithm
ranks hosts for creating Virtual Machines (VMs) and validates the processing
time of VMs and places theVMconsidering deadline of tasks, VMs can be placed
in an increasing order of their respective processing time. Then, the decision for
migrating VMs to other hosts is evaluated using Markov decision model. Through
this process, for specific virtual machine necessities of workloads, we can reduce
the number of hosts. The proposed algorithm is simulated in Cloudsim shows that
it improves the workload consolidation quality, and is appropriate for deadline
task consolidation in cloud data center.
Keywords: Cloud data centers; Consolidation; Energy efficiency; Deadline; Virtual Machine.
SIP Based VOIP Anomaly Detection Engine using DTV and ONR
by Saira Banu
Abstract: Voice over Internet Protocol (VoIP) has gained more attention in the recent years due to its advantage of cheap calls when compared to the existing PSTN network. The callers such as the advertiser, telemarketers, prank callers who make use of this VOIP for generating the anomaly calls and messages are characterized as SPIT. The Previous work was focused on callee feedback to block the spam callers. The proposed technique detects the anomaly in the call pattern without user involvement i.e the pre-acceptance method. This SIP- based approach relies on direct trust value score (DTV) and online network reputation (ONR) of the caller to detect the anomaly calls and block the spammer.
The parameter call duration , call count with frequency and the unique partner of the caller are used to compute the direct trust value of VOIP user. The ONR depicts the user behavior in the digital shopping. The online shopping behavior of the sender insists on the ONR value .The aggregation algorithm uses the DTV and ONR to measure the global reputation of the caller. This calculated global reputation value detects the anomalies and segregate the non-legitimate user during call setup using the session initiation protocol .The proposed system detects the spammer without analyzing the content, without getting feedback from the user and before connecting the call.
Keywords: KEYWORDS— (VoIP) Voice Over Internet Protocol; (SPIT) Spam Over Internet Telephony; (DTV) Direct Trust Value; (ONR) Online Network Reputation; online shopping; Global Reputation.
CLASSIFYING THE MALWARE APPLICATION IN THE ANDROID BASED SMART PHONES USING ENSEMBLE ANFIS ALGORITHM
by B.P. Sreejith Vignesh, M. Rajesh Babu
Abstract: Now days the Android based smartphones are fastest gaining in the market to date. Due to its open architecture and ease of application programming interfaces (APIs)it becomes fertile dregs for hackers to deploy malware application. This result in the burglary of personal information those are stored in Smartphones, without the user knowledge unauthorized sends unintentional short message, and if the infected smart phones operate remotely it leads ways to some other malware attacks. However, many defense mechanisms were introduced against Android malware, it results in inaccuracy of classification.The contribution of this paper to detect and classify the malwares in the manifest file based on ensemble adaptive neuro-fuzzy inference system (ANFIS) technique .This proposed system is divided into three main steps to detect the malware applications they are: 1) features are extraction using the method called Principal Component Analysis (PCA) method, 2) feature selection, using Pearson Correlation Coefficient (PCC) method and 3) malware applications are classified, using ensemble of ANFIS technique.The proposed system produced the best detecting malware applications classification and accuracy will be highly efficient than the other classification techniques.
Keywords: Android; ANFIS; Malware application; Pearson Correlation Coefficient for Entropy in the Information Gain Principal Component Analysis (PCA).
Hybrid Model for Enhancement of Passenger Information Management System
by Munir Kolapo Yahya-Imam, Sellappan Palaniappan, Seyed Mohammadreza Ghadiri
Abstract: The current booking models (systems) used by interstate bus transport service providers (operators) in Nigeria have two major drawbacks: (1) poor management of traveler information and (2) high operating costs. Although attempts have been made to address these issues, the models are far from satisfactory. The booking (and reservation) processes are still cumbersome and time consuming. Thus, there is an urgent need for an enhanced booking model. This paper presents an improved model using Dijkstra Algorithm (DA) and Demand Responsive Transport (DRT) technique. The model has three components: services, techniques, and service providers. A purposive and selective sampling technique was used to gather data from 20 interstate bus transport operators and analysis of the data confirmed the need for such an improved booking model.
Keywords: DRT; Dijkstra; Heuristic; Booking; Reservation; Bus Transport.
Energy Based Efficient Authenticated Routing Protocol For MANETs for DDOS attacks with minimized power consumption
by M. Savithri, M. Rajesh Babu
Abstract: In MANET, reliable and secure communication is the most challenging task. Mobile Ad hoc Network (MANET) is characterized by mobile hosts, dynamic topology, multi-hop wireless connectivity and infrastructure less ad hoc environment. Limited resource availability such as battery power and security are the major issues to be handled with mobile ad hoc networks. An attacker can easily disrupt the functioning of the network by attacking the underlying routing protocol. Hence, security in ad hoc networks is still a debatable area. In this paper, we have proposed Energy Based Efficient Authenticated Routing Protocol (EBEARP) for mobile ad hoc networks. Our protocol provides efficient security against route discovery attacks using hop-by-hop signatures. It quickly detects the malicious nodes, thus assisting the nodes to drop the invalid packets, earlier. It also uses an efficient node selection mechanism, which maximizes network life time and minimizes power consumption. With the help of detailed simulation studies, we show that EBEARP provides better packet delivery ratio with minimized energy.
Keywords: Energy Based Efficient Authenticated Routing Protocol (EBEARP); MANET; secure communication.
Energy Aware Clustered Load Balancing in Cloud Computing Environment
by K. R. Remesh Babu Raman, Philip Samuel
Abstract: Cloud is a collection of datacenters with heterogeneous resources, which gives services to the users based on pay-as-you-use model. Even though it has several advantages such as availability, scalability, and reliability, but some performance parameters such as energy consumption, load balancing, response time, resource allocation time, etc., are not properly fine tuned. Most of the research articles published so far concentrates on any one of the above issues and fails to consider other parameters. This paper proposes an energy aware clustered load balancing system in which, heterogeneous resources are clustered into different clusters by using a partitioning based clustering algorithm. Clustering reduces the number of resources needs to be searched and hence reduces the total searching time required for resource discovery and allocation. In the next phase an energy aware best-fit virtual machine (VM) allocation is carried out. The weight value of resources is calculated based on its memory, storage and processing capacity. Then corresponding VM cluster is found out using this weight value. If the resources are available in it, then allocate it, else goes to second portion of that cluster and check for the availability. If the VM is unable to allocate in that cluster, then only the system consider other clusters. In the final step, a best-fit allocation strategy is used for allocating processes to the VMs. By using the best-fit algorithm, efficient VM placement is done for optimal space utilization. The results shows that proposed energy aware clustered load balancing method, reduces time for resource discovery, resource allocation and response time with power consumption.
Keywords: Cloud computing; VM scheduling; Best-fit algorithm; Energy consumption; Load balancing; Resource allocation.
Semantic Clustering approach for documents in distributed system framework with Multinode setup
by Priyadarshini R., Latha Tamilselvan
Abstract: Todays era is rather called big data era, data starts growing from different sources of web and such scalable data is very hard to manage with the existing frameworks and technologies. Content management provides useful information compared to data management in web. Wikipedia is one such content management system where the article posted has number of source documents. Perhaps it is very difficult to search a exact relevant document for selected content in an wikipedia article as it has too many sources such as primary, secondary and tertiary. In order to search and retrieve relevant document in the growing content, clustering of documents using similarity analysis is very much essential. This process involves implementation of different types of machine learning algorithms and clustering algorithms on the large volume of data. Existing system offers a clustering technique based on term and inverse term frequency (TfDf) scoring method of the keyword in the document which decides the similarity with the source document . The same set of documents is also clustered using K-Means clustering algorithm along with concept matching. The relevancy score is calculated for the matched documents in the cluster correspondingly . This work proposes a new clustering method for distributed framework. It also uses the existing method of keyword term frequency for analysis of large scale documents. Initially a test bed is created with multi-node storage in Hadoop environment and keyword based clustering is implemented for huge amount of data. In addition to this Semantic Agglomerative Hierarchical (SHA) clustering algorithm is proposed to retrieve similar source documents accurately for a selected content in the virtual document. Recall and precision is calculated for the different sets of documents using keyword based clustering and SHA. Comparison of time taken for single node and multinode upload, search and retrieval are also analyzed.
Keywords: clustering; multinode setup; hadoop; semantic retrieval; similar documents rn rn.
AN EFFICIENT 3D IMAGE EXTRACTION TECHNIQUE FOR BUILDING INFORMATION MODELING IMPORT
by Feng Cui
Abstract: Building Information Modellingalso popularly known as the BIM is emerging to be one of the most rapidly advancing modelling techniques used in a wide range of applications. BIM drastically reduces the time involved in manual work which is characteristic of the past and completes automates the process of managing and disbursing required data for modelling and construction of civic structures. There has been a widespread investment in BIM by clients prior to commencement of new projects, pre construction analysis, interior designing and post construction. Since BIM is a recent trend, the motivation for the proposed work has been derived an exhaustive literature survey in key areas for research contributions which could greatly increase the quality and importance of BIM. The proposed work focuses on the input side of BIM system involved with acquisition and processing of information before being exported into the database management system. 3D to 2D modelling and feature extraction has been proposed in this paper with dimensionality reduction technique which drastically reduces the feature data set before being exported in to the BIS management system. A Principal component analysis (PCA) has been implemented in this paper and the two dimensional features have been exported into the BIM database. The most appropriate texture image is selected from aerial images according to geometry between building faces and external parameters of thephotos. The method has been tested with LIDAR data of two building images and extraction accuracy determined.
Keywords: 3D image modelling and extraction; Polgonization; multi resolution approximation; feature import in BIS.
Research on the intellectual traffic flow control system based on multi-agent along with self-governing vehicle and System of Wireless Sensor Network
by Chengtao Cao
Abstract: The manuscript proposes a novel way to deal with progressively deal with the movement lights cycles and stages in a secluded crossing point. The objective of the work is a framework that, contrasting and past arrangements, offers enhanced execution is adaptable and can be actualized on not well designed components. The test here is to locate a successful outline that accomplishes the objective while maintaining a strategic distance from computationally costly arrangements. The proposed framework joins the upsides of the wireless sensor network, for example, simple organization and upkeep, adaptability, ease, non-obtrusiveness, and versatility, with the advantages of utilizing quad parallel fuzzy regulators, at is improved execution, adaptation to non-critical failure, and backing for stage particular administration. Reproduction results demonstrate that the proposed framework beats different arrangements in the writing, altogether sinking vehicles holding up times. A contextual analysis of the proposed improvement procedure is tended to by demonstrating the usage process of a self-governing driving framework. With a specific end goal to depict the usage process instinctively, center self-governing driving process that depend on the confinement, acuity, planning, vehicle controller, and framework administration are quickly acquainted and connected with the execution of a self-governing driving framework. We can inspect the upsides of conveyed framework design and the proposed advancement process by directing a contextual investigation on the self-governing framework execution.
Keywords: Road traffic; traffic flow control; Self-governing vehicle; development process; distributed system; acuity; Scheduling.
A Novel Framework for Very High Resolution (VHR) Remote Sensing Image Change Detection
by Jie Li, Ning Sun, Jianlong Zhang
Abstract: This paper proposes a novel framework for very high resolution remote sensing image change detection. The change detection technology is the goals or the phenomenon conditions of different time interval to the change that have analyzed the recognition and computer image processing system, including judgment goal whether changes, to determine changes the region and the time and spatial distribution of pattern category and appraisal change of distinction change. Over the past few years, researchers from all over the world have devoted themselves to the research of change detection technology. Many detection methods based on remote sensing images have been developed successively. However, no change detection method has absolute superiority in present research. This paper obtains the inspiration from PSO and OTSU to propose the particle swarm optimization segmentation jointed model to construct the optimal solution of generating change map and the PSO jointed OTSU is introduced to help obtain the optimal threshold. Numerical simulation proves that the proposed method can segment the changed regions accurately while keeping the high noise robustness.
Keywords: Very High Resolution; Remote Sensing; Wireless Sensing; PSO; OTSU; Change Detection.
Certain investigations on effective rate adaptation in cognitive radio with channel characteristics
by Suseela Bhaskar, D. Sivakumar
Abstract: The role of cognitive radio is finding the unused spectrum and providing effective transmission. This has been investigated with the concept of multi-user multi-channel capability in terms of protocols in this work. The problem of lack of synchronization among user leads to ineffective transmission among secondary users. This is much worse in the case of fading channel. So two protocol one based on Multi User Multi Channel Particle Swarm Optimization based Cognitive Radio (MUMC-PSO-CR) were the rate adaptation has been done with particle swarm optimization technique and other Multi User Multi Channel Tree Seed Algorithm Cognitive Radio (MUMC-TSA-CR) were rate adaptation has been done with tree seed algorithm. MUMC-TSA-CR protocol implements a simple statistical analysis for the criteria of forwarding without congestion.
Keywords: Rate Adaptation; Congestion Avoidance; Effective transmission.