International Journal of Enterprise Network Management (24 papers in press)
Labor productivity improvement using hybrid Maynard Operation Sequence Technique and Ergonomic assessment
by Medha LNU, Sharath Kumar Reddy, Vimal KEK, Aravind Raj Sakthivel, Jayakrishna Kandasamy
Abstract: Productivity measures how efficiently productions inputs, such as labor and capital, are being used in an economy to produce a given level of output. With growing competition across the globe, contemporary organizations are under pressure to exploit the untapped potential of the labour. Maynard Operation Sequence Technique (MOST) is a work measurement system that can be easily implemented and practically maintained. The basic ergonomic analysis was also conducted for understanding the interactions among the labour and other elements of a system to optimize human well-being and overall system performance. In this article, MOST is used for time measurement study and minimization of fatigue among the operators by using ergonomics in a stamping unit. The primary objective of this review was to reduce the motion of a task in order to reduce the effort and time to perform the task to achieve higher production and better service level by the ergonomic approach. Ergonomics accounts the user's capabilities and limitations to ensure that tasks, functions, information, and environment suit each operator in any organization. Scoring sheets approach was used in conducting ergonomics study to decide the fitness of any unit on the basis safety and posture analysis of the operator. The hybrid approach (MOST-Ergo) can be used to improve the productivity of any organization by reducing the time and fatigue consumed by the operator during the operation.
Keywords: maynard operation sequence technique; MOST; time study; standard time; productivity; ergonomic work posture analysis.
Context-sensitive contrastive feature-based opinion summarization of online reviews
by Lavanya Sk, Parvatha Varthini
Abstract: Online reviews discuss one product at a time. It becomes a time consuming process for a user to compare and contrast two or more products. Contrastive Opinion Summarization was introduced to help users by producing a useful contrastive summary. A new COS approach called Context-Sensitive Contrastive Opinion Summarization is introduced in this paper. This method extracts feature and opinions of a product based on context term in a sentence and compare them with opinions of another product to develop a brief summary comprising of contrastive feature-opinion pair. Traditional COS methods rely on content similarity and contrastive similarity functions based on simple semantic term matching using WordNet. To perform in-depth semantic analysis, more advanced similarity functions are needed. A clustering algorithm is proposed which adds context- similarity into PLSA model in semantic term matching by incorporating context priors from Conceptnet. In addition the algorithm attempts to align contrastive feature-opinion pair in each cluster to generate a contrastive summary about different products. Compared to previous methods, the proposed model can integrate context sensitivity and better align the contrastive opinion pair for producing better arguments summary. Experimental were conducted over the benchmark UCI Machine Learning Repository Car Data Sets and the results exhibit the usefulness of the context- similarity over the baseline content similarity and contrastive similarity measures.
Keywords: Feature based Opinion Summarization; Contrastive summary; Contrastiveness; Representativeness;Context-aware sentiment analysis.
Owner-managers perceptions of corporate social responsibility practices within small and medium-sized accounting firms - an Australian study
by Sujana Adapa, Josie Fisher
Abstract: This article explores conceptualisations of Corporate Social Responsibility (CSR); perceptions of its importance; and practices implemented by owner-managers of Small and Medium Sized Enterprises (SMEs) in Australia. Qualitative in-depth interview data was obtained from 17 owner-managers of small and medium-sized accounting firms operating in Sydney. Inductive content analysis was conducted by the researchers to identify the concepts and themes of importance by using Leximancer qualitative text analytical software. The results revealed that the owner-managers of these firms were aware of the basics of social responsibility and recognised that the adoption of responsible business practices contributes to business success. The owner-managers perceptions of the practices of CSR varied based on the firm size that resulted in the emergence of an additional category of family-owned firms. Additionally, a subset of small micro-sized firms also emerged on the basis of their CSR practices and unique orientations towards the concept of CSR as highlighted by the owner-managers of the accounting firms in Sydney. As outlined by the owner-managers of the small and medium-sized firms in the study, retaining market position seemed to be critical in the adoption of CSR practices in accounting firms. Thus, a majority of the small and medium-sized accounting firms included in the study sample seemed to adopt reactive CSR practices to retain their market position, although very few engaged in following proactive CSR practices.
Keywords: corporate social responsibility; small and medium-sized firms; owner-managers; stakeholders; firm size; accounting.
MAXIMISING THE EFFICIENCY OF KEYWORD ANALYTICS FRAMEWORK IN WIRELESS MOBILE NETWORK MANAGEMENT
by Geetha Kannan, Kannan A
Abstract: Nowadays, data analytics in spatial database objects are associated with keywords. In the past decade, searching the keyword was a major focusing and active area to the researchers within the database server and information Retrieval community in various applications. In recent years, the maximizing the availability and ranking the most frequent keyword items evaluation in the spatial database are used to make the decision better. This motivates to carry out research towards of closest Keyword Cover Search. Which, is also known as Fine Tuned keyword cover search methodology, it considers both inter-object distance and keyword ranking of items in the spatial environment. Baseline algorithm derived in this area has its own drawbacks. While searching the keyword increases, the query result performance can be minimized gradually by generating the candidate keyword cover. To resolve this problem a new scalable methodology can be proposed in this paper.
Keywords: Information retrieval; Keyword searching; Nearest Neighbor; Point of Interest; Spatial database.
IMPROVING MECHANICAL STRENGTH ON WELDED JOINTS BY USING OPTIMIZATION TECHNIQUE
by Pandiyarajan R
Abstract: The welding process is an important component in many industrial operations. Welding input parameters play a very significant role in determining the quality of a weld joint. The joint quality can be defined in terms of properties such as weld-bead geometry, mechanical properties, and distortion. Generally, all welding processes are used with the aim of obtaining a welded joint with the desired weld-bead parameters, excellent mechanical properties with minimum distortion. So that in this paper presents find the suitable input parameter in welded joints and then find the full penetration of the material. By using on design of experiment (DOE), Genetic Algorithm algorithms and computational network are widely used to develop a mathematical relationship between the welding process input parameters and the output variables of the weld joint in order to determine the welding input parameters that lead to the desired weld quality of the welded material.
Keywords: Welding; DOE; Parameter Optimization; GA; Regression Equation.
A Study on the Impact of Psychological Empowerment on Motivation and Satisfaction among the Faculty Working in the Technical Educational Institutions in India based on Age and Work Experience difference
by Prabha Mariappan, Punniyamoorthy Murugesan, Nivethitha Santhanam
Abstract: The purpose of this study is to investigate how the impact of PE on motivation and satisfaction varies according to the faculty members age and work experience. Data were collected from 402 faculty members employed at technical institutions across India. From the results of the study, it is evident that faculty members with above average age exhibited higher PE, motivation, and satisfaction. Subsequently, faculty members with above average experience possessed a higher level of PE and satisfaction. Further, the implication of these findings suggests that the proposed framework will act as a benchmarking tool to measure the psychological empowerment among the faculty members.
Keywords: Psychological Empowerment; Age; Work experience; Faculty.
A Study on the Impact of Macroeconomic Indicators on the Stock Price by relaxing the Assumptions of Stationary in Time series Data in a General Linear Model
by M.I. Nafeesathul Basariya, Punniyamoorthy Murugesan
Abstract: A model has been evolved by keeping the stock index as dependable variable and Gross Domestic product, Consumption and Consumer Price Index as independent variables. The assumptions to arrive the model are tested. The behavior of the model is studied by including and relaxing the important assumption of stationarity in the economic data. It was finally found that the model becomes significant if we violate the stationary assumption for both dependent variable stock price and independent variable Consumer Price index, Consumption and Gross Domestic Product. This is evidenced by demonstrating the model by using the data related to the macroeconomic variables of Developed countries USA, UK, Emerging countries India and Brazil, Frontier Countries Latvia and Estonia.
Keywords: Consumer Price Index; Consumption; Gross Domestic Product; Stock Prices; Stationarity.
Mechanical Integrity of PEEK Bone Plate in Internal Fixation of Femur: Experimental and Finite Element Analysis Towards Performance Measurement
by Navid M.P.Davani.K, ELANGO NATARAJAN, Balaji Raghavendaran Hanumandarao, Sivakumar Paramasivam
Abstract: Internal fixation is a surgical method used to stabilize the fractured bone in order for a proper callus formation. Many materials, including stainless steel and titanium, have been used in prosthetic plates. The studies show problems associated with the use of metals plates due to mismatch of stiffness of the bone and prosthetic plate. The effect of this phenomenon, called stress shielding could be seen not only at the healing region but also in the entire bone itself. Therefore, modern materials, especially polymers, with a stiffness close to the human bone have been devised to transfer more compressive stress to the bone. Of the existing biomaterials, PEEK (poly-ether-ether-ketone), has become an excellent alternative to metal plates. The aim of this research is to investigate the effectiveness of PEEK plate in stress transformation into the fractured bone and to conduct performance measurement between PEEK and Steel. Uniaxial tensile test and fatigue tests are conducted as per ASTM standards to measure mechanical properties such as tensile strength, modulus of elasticity and fatigue strength. The measured mechanical properties of PEEK are further applied in finite element analysis to measure the stress transformation between plate and femur bone. Fatigue analysis is also carried and the simulation results reveal that PEEK plate is more desirable in terms of reducing stress shielding in the femur than that of stainless steel. Taguchis single response analysis is used to optimize the process parameter and material selection. The weight reduction and cost reduction are also observed. It is perceived from the Taguchi analysis that the PEEK is the best appropriate selection than SS316L for stress transformation in to the fractured bone in inducement of principal stress and shear stress point of view. A graph between principal/shear stresses and material/distances are plotted to verify the input dependency. It is evident from the plots that the PEEK performs well at initial and decreases at later, which is due to more negative stress.
Keywords: femur; stress shielding; prosthetic plate; internal fixation; biocompatible; fractured bone; thermoplastic; internal fixation.
A literature review on the anomalies observed in the newsvendor ordering behaviour
by S. Yamini
Abstract: In a classical newsvendor setting, the retailer places an optimal order quantity by finding a trade-off between overstocking and understocking of products. However, it has been observed that the managers do not always order an optimal quantity while making inventory decisions, due to influence of various behavioural biases. Infact, the evidences say the experienced managers also exhibit this tendency. In the early 2000s, researchers in the area of behavioral economics have taken roots to analyse the behavioral dynamics influencing the inventory ordering decisions in newsvendor settings. Later, a large number of research studies has focused its attention on understanding the cognitive biases and heuristics involved in the process of inventory decisions. The research has then progressed in the direction of understanding the role of learning dimensions and information acquisition in making better inventory decisions. Further, researchers have also found if the individual heterogeneity such as gender differences, cultural differences, and hierarchical differences influence the ordering pattern of individuals. Infact, few research studies focus on the impact of cognitive reflection and other individual traits on the stocking decisions of the newsvendor. Another class of literature looks at the anomalies observed in various non-conventional newsvendor settings such as newsvendor ordering multiple items, simultaneously setting the price while ordering and placing order when the competition prevails. This article provides a detailed summary of the research progress in the behavioural newsvendor problem. It also provides a framework of the existing literature and identifies the research gaps to point to future research possibilities and priorities. The framework gives a systematic approach to confirm the existence of a substantial scope of research opportunities and points to specific areas for further research.
Keywords: Behavioural Economics; Behavioural Operations; Experimental Economics; Newsvendor ordering; Bounded Rationality; Cognitive biases and heuristics.
A development in the existing Non-Linear model and to study its impact on the Nash equilibrium in a two-person non-zero sum game
by Sarin Abraham, Punniyamoorthy M
Abstract: A non-zero sum two-person game can be formulated as a non-linear program problem for finding the Nash equilibrium. Although intensive research has been done in developing methods for solving such non-linear problems, very less work has been done in modifying the existing model in order to generate a more refined Nash solution. The study focuses on modifying the nonlinear programming model by incorporating some additional constraints and analyzing if the altered model would generate a better result. The utility of the additional constraints is discussed, in terms of the payoff received by either of the players, for different problem situations.
Keywords: Non-Linear Programming; Nash Equilibrium; Optimality; Feasible Solution Space.
Designing an Integrated Multi-Channel Multi Product Closed Loop Sustainable Supply Chain Network Meeting Customer Requirements
by T. Niranjan, P. Parthiban
Abstract: Indian manufacturing firms which started by focusing on offline exclusive sales (single channel), are expanding their sales to online domain (multi channel) today. They still facing lot of difficulties in interfacing various channels efficiently in their multi channel supply chain network, this integration of different channels increases its customers range to purchase and customer comfort. Consideration of green and recycling concepts in supply chain has become essential due to consumers demand for products which are eco-friendly and also strict government regulations. This paper aims to develop a multi product closed loop supply chain model for an Indian kitchen ware firm to address their integrating issues between multiple channels take into consideration the environmental and economic sustainability. IBM CPLEX optimizer is used to solve the model for minimising the transportation cost between various stages of supply chain and the emissions from plant and vehicles. To take into account the real world factors of customer behaviour, four types of customer zones are selected to accommodate different customer choices. The results show how the optimal supply chain structure is affected by these multi channel customer preferences.
Keywords: Sustainable; supply chain; multi-channel; closed loop.
Network and Government Intervention influencing Sustainability and Business Growth of SMEs: A study with Indian MSMEs
by Maitreyee Das, K. Rangarajan, Gautam Dutta
Abstract: The role of corporate sustainability in driving business performance has been well researched in the case of big corporations for developed nations. But in the case of small and medium enterprises (SME) very limited research has been conducted to explore the business benefit derived out of sustainable business practices. In spite of their contribution to the economy, most of the SMEs fail to maintain a sustainable growth path in the long run. The current paper tries to estimate how effective utilization of their business network and government intervention influences the growth of SMEs through their sustainability performance. A self-administered questionnaire was developed and responses were collected from 200 SMEs in and around Kolkata. The data was analysed using Partial Least Square techniques of Structural Equation Modeling in SPSS. Results showed that both government intervention and network utilisation positively influence business growth of SMEs through their social and environmental sustainability. Also, the size of capital investment has a moderating effect on the strength of this relationship. The practical implication of the model in the Indian context has also been discussed along with future research possibilities
Keywords: Small and Medium Enterprises; Corporate Sustainability; Sustainable Business Growth; Social and Environmental practices; business performance; Network; Collaboration; Government intervention.
Special Issue on: BDSCC-2018 Big Data Innovation for Sustainable Intelligent Computing
A Collaborative Defense Protocol against Collaborative Attacks in Wireless Mesh Networks
by Diana Jeba Jingle, Mano Paul P
Abstract: Wireless Mesh Network is an evolving next generation multi-hop broadband wireless technology. Collaborative attacks are more severe at the transport layer of such networks where the transmission control protocol's three-way handshake process is affected with the intention to bring the network down by denying its services. In this paper, we propose a novel Collaborative Defense Protocol (CDP) which uses a handshake-based verification process and a collaborative flood detection and reaction process to effectively carry out the defense. This protocolpresentsa group of monitors that collaboratively entail in defending the attack; thus reduces the burden on a single monitor. Moreover, this paper proposes a novel transport layer Post-connection flooding attack that occurs after establishing a TCP connection and we show that CDP can detect and mitigate this attack.The CDP protocol has been implemented in Java and its performance has been evaluated using essential metrics. We show that CDP is efficient and reliable and it can identify the attack before any major damage is occurred.
Keywords: Collaborative attack; handshake-based; request packets; regular packets; connection flooding.
Special Issue on: Applications and Innovations of Enterprise Networking Management in Social Commerce
NEURO FUZZY COGNITIVE CONNECTION FUNCTIONAL POINT FOR ENTERPRISE NETWORK MANAGEMENT
by Frankvijay J.
Abstract: Software Effort Estimation (SEE) is one of the vital role in enterprise managment because it helps to predict amount of effort provided to particular process. This created SEE process used to minimize the incomplete data involvements, uncertainty and other mis-behaviors effectively. The SEE process consumes project plans, pricing information, investment details, budget and iteration plan as input and the SEE produces the exact effort for the particular enterprise details. During the process, the SEE may require large amount of data, which increases the efficiency of the effort estimation system. So, in this paper introduces the enterprise data analytics process by using the size and judgmental software effort estimation process. This method analyzes the effort in terms of using experts opinions, use case, functional points, and software size unit information. In addition to this, the method evaluates the neuro fuzzy cognitive connection based functional points are used to estimates the effort with effective manner. This method examines the connectivity between one requirement to another requirements and it constructs the relationship graph that eliminates the incomplete requirements and details successfully. The connectivity based functional point analyze process reduces the time for examining the software effort. Then the performance of the system is calculated with the support of experimental results such as MRE and VAF.
Keywords: Software Effort Estimation; size and judgmental software effort estimation process; enterprise in software; neuro fuzzy cognitive connection based functional points; MMRE and VAF.
CAMELS MODEL ANALYSIS FOR DISTRICT CENTRAL CO-OPERATIVE BANKING ENTERPRISES IN ANDRA PRADESH
by SATHYA V., Oliver Bright A.
Abstract: CAMELS is a perceived worldwide rating framework to evaluate the relative money related quality of banking enterprises and to propose essential procedures to enhance shortcomings of banking enterprises. In Andhra Pradesh before detachment of Telangana State, there were 22 DCCBs (District Co-operative banking enterprises) in Andhra Pradesh State Cooperative Bank. For breaking down similar execution of the DCCBs in Andhra Pradesh, CAMELS Model has been utilized for the (CAGR compound yearly development rate) of 12 years (2002-2003 to 2013-2014) and from that point, thorough rank test and factual measures have been utilized. CAMELS remain for Capital Adequacy, Asset Quality, Management Efficiency, Earnings Capacity, Liquidity, and Sensitivity. CAMELS' proportions have the imperative imperativeness to feature the sound money related position and additionally the wellbeing of the DCCBs of the co-agent DCCB through smaller scale investigation of an asset report and pay explanation things.
Keywords: CAMELS; Andra Pradesh; Cooperative bank; Micro Analysis.
Study and prioritizing factors of Productivity of the Employees of Steel Manufacturing Industry, Kanjikode by extended ACHIEVE Model
by Vinu V G., Oliver Bright A.
Abstract: Employee productivity is a key factor for the success of manufacturing companies. Employees are an asset that cannot be imitated by other resources, and unfortunately, they are also the hardest to control. Performance improvement initiatives with a wide range of approaches are used in an attempt to improve employee productivity. Incentives or organizational climate improvement are some examples of such programs. However, most of these studies take only one or two factor into consideration, which may not provide a comprehensive solution to the productivity problem they face in many cases. An extended ACHIEVE model by the name MACHIEVE model has been proposed to overcome this, with additional factor M - Material. Analysis of the components of labor productivity based on this new MACHIEVE model has been performed among employees in the Steel manufacturing Industry in Kanjikode. This is a Structural Equation Modelling analysis in which the sample consisting of 420 working personnel in a different workgroup in Steel manufacturing Industry in Kanjikode were selected from 1280 employees through stratified random sampling. The survey tool included labor productivity questionnaire of MACHIEVE model. The data were analyzed by AMOS-23 software and the mean scores for MACHIEVE model variables are calculated. The results indicated that the eight factors of MACHIEVE model have an impact on increasing employee productivity. The analysis also suggested that the two factors C-Clarity and H-Help had the greatest impact on labor productivity in the viewpoint of the staff.
Keywords: ACHIEVE; MACHIEVE; Productivity; Employees; Steel Manufacturing.
Special Issue on: Sustainable Computing for Enterprise Resource Planning Applications
Mining massive online location-based services from user activity using best first gradient boosted distributed decision tree
by M. Venkatesh, V. Mohan Raj, Y. Suresh
Abstract: User activity is predicted through the frequency in which the online substances in location-based social networks (LBSN) are produced and used by the consumer. Users are classified by researchers into a number of groups depending upon the level of their functioning. This work involves gradient boosted distributed decision tree (GBDT) which is optimised on the basis of total iterations and shrinkage on using best algorithm. Implementation of the data is done through Hadoop network. A foursquare dataset is created using work, food, travel, park and shop. One of the most commonly used machine learning algorithm is stochastic gradient boosted decision trees (GBDT) at present. The node with lowest lower bound is developed through best first search (BFS). Its own filing system is provided through Hadoop which is called Hadoop distributed file system (HDFS). The algorithm used is K-nearest Neighbour (KNN) classifier algorithm.
Keywords: user activity; foursquare dataset; stochastic gradient boosted decision trees; GBDT; best-first search; BFS; K-nearest neighbour classifier; KNN; social network; location-based social networks; LBSN; big data; Hadoop network; Hadoop distributed file system; HDFS.
GRO and WeGO - algorithmic approaches to integrate the heterogeneous databases and enhance the evaluation of ontology mapping systems in the semantic web
by V. Rajeswari, M. Kavitha, Dharmishtan K. Varughese
Abstract: In the present day world, where information driven economy and information enhanced living standards rule everything, the sources of data from which the information is derived, are highly heterogeneous. The heterogeneity necessitates a mechanism for integrating data, before it is presented to the user. The internet and WWW are forming the backbone of information. Semantic web is an initiative in achieving the goal of 'machine processed information' being available to us than requiring human intelligence for processing information. This work is carried out to address the heterogeneity problem that exists among data sources and provides a solution through the application of ontology. Ontology is a conceptual tool for handling semantic heterogeneity. The algorithmic approach is adopted in the mapping solution system. The elements of ontology are compared and similarity analysis is carried out to arrive at the degree of matching of individual nodes as well as the ontology in totality for an ontology alignment.
Keywords: ontology; semantic web; heterogeneous databases; GRO; WeGO.
Feature selection and instance selection using cuttlefish optimisation algorithm through tabu search
by V. Karunakaran, M. Suganthi, V. Rajasekar
Abstract: Over the recent decades, the amount of data generated has been growing exponentially, the existing machine learning algorithms are not feasible for processing of such huge amount of data. To solve such kind of issues, we have two commonly adopted schemes, one is scaling up the data mining algorithms and other one is data reduction. Scaling up the data mining algorithms is not a best way, but data reduction is fairly possible. In this paper, cuttlefish optimisation algorithm along with tabu search approach is used for data reduction. Dataset can be reduced mainly in two ways, one is the selecting optimal subset of features from the original dataset, in other words eliminating those features which are contributing lesser information another method is selecting optimal subset of instances from the original data set, in other words eliminating those instances which are contributing lesser information. Cuttlefish optimisation algorithm with tabu search finds both optimal subset of features and instances. Optimal subset of feature and instance obtained from the cuttlefish algorithm with tabu search provides a similar detection rate, accuracy rate, lesser false positive rate and the lesser computational time for training the classifier that we obtained from the original data set.
Keywords: data reduction; instance selection; feature selection; cuttlefish optimisation; tabu search.
Enterprise big data analysis using SVM classifier and lexicon dictionary
by S. Radha, C. Nelson Kennedy Babu
Abstract: The emergence of the digital era has led to growth in various types of data in a cloud. In fact, there may be three fourth of the total data will be treated as big data. In many organisations, massive volume of both structured and unstructured data sit idle. Various categories of data are complex for pre-processing, analysing, storing and visualising. Cloud computing provides suitable platform for big data analytics for the storage and for predicting customer behaviour to sell products. Unstructured data like emails, notes, messages, documents, notifications and Twitter comments (including from IoT devices) remains untapped and is not stored in a relational database. Valuable information on pricing, customer behaviour and competitors may be inhumed within unstructured data. This makes cloud-based analytics as an effective research field to address several issues and risks need to be reduced. So we propose a method to extract and cluster sentiment information from various types of unstructured text data from social networks by using SVM classifiers combined with lexicons and machine learning for sentiment analysis of customer behaviour feedback. The method has performed efficient data collection, data loading and efficiently performs sentiment analysis on deep and hidden web.
Keywords: deep web mining; sentiment analysis; big data; unstructured data; map reduce; hidden information; big data analytics; text mining; clusters; enterprise data.
An optimised neural network-based spectrum prediction scheme for cognitive radio
by B. Bhuvaneswari, T. Meeradevi
Abstract: A cognitive radio (CR) technology enables all the users to utilise spectrum without interference. There will be a spectrum sensing for all the non-authorised users to perceive the other possibilities of getting a channel. The traffic feature will be unknown to be a priori to design the spectrum predictor with the back propagation (BP) neural network (NN) model and the multi-layer perceptron (MLP).This work proposed an optimised neural network to obtain improved results. The BP algorithm will not require prior knowledge of the real world problems that are trapped within the local minima. This is used widely to solve the problems and found in literature as an evolutionary algorithm like the bacterial foraging optimisation algorithm (BFOA) used for the MLP NN for enhancing the process of learning and improving the rate of convergence as well as accuracy of classification. Performing this spectrum predictor will be analysed using some extensive simulations.
Keywords: spectrum prediction; cognitive radio; CR; neural networks; NN; multi-layer perceptron; MLP; back propagation; BP; bacterial foraging optimisation algorithm; BFOA.
An improved downlink packet scheduling algorithm for delay sensitive devices in both H2H and M2M communications in LTE-advanced networks
by S. Radhakrishnan, S. Neduncheliyan, K.K. Thyagharajan
Abstract: The demand for increased data rate with improved QoS for real-time data traffic is ever increasing in the present day wireless environment. The scheduling schemes available in the literature incur lot of scheduling overhead at the eNodeB. Therefore, this work recommends an energy efficient, QoS-aware scheduler with reduced scheduling complexity at the eNodeB, for transmission of delay sensitive data. The scheduling problem is composed as a gain of weighted transmission rates of all possible combinations of various resources required by the channel for transmitting data. An improved greedy algorithm at the eNodeB, has been developed to allocate the resources dynamically to the user equipments (UEs) for the transmission of real-time data. The input video frames to the algorithm are compressed using discrete wavelet transform. The results of this research work show that the proposed scheduling algorithm greatly improves the coverage of the cell edge users. The performance of this greedy scheduler is compared with other two notable schedulers in the literature namely LOG rule and EXP-rule. This scheduling algorithm outperforms the other schemes in terms of QoS parameters for real-time data transmission.
Keywords: LTE-advanced; greedy algorithm; downlink packet scheduling; CA; multi input and multi output; MIMO; M2M; QoS.
Special Issue on: Cloud Computing in Enterprise Network Management
An Attempt to Enhance the Time of Reply for Web Service Composition with QoS
by Karthikeyan Sivasamy, Meenakshi Devi P
Abstract: The web services are the commonly prevailing service clusters of the service oriented framework (SOA) and service related assessments. The disputes are related to the quality of service (QoS) for choosing web services freely and creating a collection of web services for carrying out trades. The ultimate aim is to choose web services based on the non functional features and quality of service (QoS) ranks. The aim is to consider that these web services holds identical features for every processes along which they hold varying non functional features and quality of service (QoS) metrics. In order to choose a web service for every process a social aspect web (SAW) scheme is employed which does not comprehensively make use of all sorts of web services. It employs the requirements of the user for ranking web service set of the applications and finally provides SAW schemes over a set of web service applicants. The mechanism helps in selecting the web services in terms of quality of services (QoS) scores and user needs. The choice of web services over varied web services based on scheme can be utilized for aggregation and organizing web services resulting in optimized time of reply to the web service actions.
Keywords: QoS; SAW; Ranks; Web Services and Non – Functional Features.
Attempting to Design Differed Service Broker Forwarding Strategy for Data Centres in Cloud Environment
by S. Prabu, S. Karthik
Abstract: The cloud computing is based on broadcasted computing resources for controlling diverse services like a server, storage and applications. The applications and models are offered in terms of pay per usage using the data centre to the users. The data centres are positioned globally and moreover, these data centres could be overloaded with the escalated number of client applications that are being serviced at the identical time and position which corrupts the comprehensive quality of service of the relayed services. Diverse user applications might need diverse customization and demands calibrating the performance of the user applications at differed resources are quite intricate. The service supplier is incapable of performing choices for the suitable set of resources. The design of differed service broker forwarding strategies is based on heuristics intended to accomplish minimal reply time based on the transmission medium, bandwidth, latencies and task size. The designed service broker strategy attempts in minimizing the overloads of the data centres by conveying the user demand to the subsequent data centres that acquire improved reply and operational time. The analysis reveals potential outcomes in terms of reply and operational time as estimated to the other exiting broker strategies.
Keywords: Service Broker; Cloud Environment; Quality of Service; Data Centres and latency.