International Journal of Ad Hoc and Ubiquitous Computing
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International Journal of Ad Hoc and Ubiquitous Computing (42 papers in press)
Abstract: A proactive document can react to its actual environment by autonomously selecting and performing actions integrated into its body and interact with its user. When migrating over a network of execution devices it may encounter diverse execution contexts, each one set up according to the temporal characteristics of a receiving device and preferences of its owner. A concept to augment proactive documents with negotiation capability is proposed to make them responsive to such dynamically changing contexts, and implemented in a system where they that can migrate as attachments to email messages, owing to a dedicated email client capable of handling them. Negotiation is based on a simple game-theoretic mechanism to minimise computation load on execution devices. Four negotiation algorithms are proposed and two of them evaluated in more detail in a series of experiments, when respectively, negotiating parties do not or do have knowledge on past encounters and negotiated contracts.
Keywords: proactive documents; dynamic execution contexts; mobile agents; multi-issue negotiations; ad hoc collaborative processes;.
Reverse-biform Game based Resource Sharing Scheme for Wireless Body Area Networks
by Sungwook Kim
Abstract: Current advances in wireless sensor technologies have contributed to the development of Wireless Body Area Network (WBAN). It has been considered for applications in medical, healthcare and sports fields. Due to specific features and reliability requirements in WBAN, a number of new challenges have been introduced to design novel WBAN protocols. In order to cope with these challenges, game theoretic approach can allow WBANs to improve their performance while increasing their flexibility and adaptability. In this paper, we develop a new WBAN resource sharing scheme based on the reverse-biform game model. Based on the dual-level phases, the limited WBAN resource is effectively shared by employing a coordinate-and-competitive game manner. In particular, we consider the unique features of WBAN applications, and provide a generalized solution for the resource sharing problem. The simulation results demonstrate that our game-theoretic framework can provide the ability to practically respond to current WBSN conditions. This approach is suitable for real WBAN operations, particularly for the energy efficiency, network throughput, and QoS provisioning.
Keywords: Wireless body area networks; Power control algorithm; Data-tuning mechanism; Quality of Service; Reverse-biform game.
Trust Management in Vehicular Ad hoc Networks: a survey
by Ilhem Souissi, Nadia Ben Azzouna, Tahar Berradia
Abstract: The vehicular ad hoc networks (VANETs) provide a variety of applications that aim to ensure a safe and comfort driving experience. These applications rely on the communication and the exchange of data between vehicles. These entities are exposed to many security threats that may affect the reliability of the provided applications. Accordingly, there is a need for a trust management scheme that has to cope with the security threats and the high dynamicity of the network topology. In this paper, we survey the recent advances in trust management for VANETs. The aim of this paper is to show the importance of an adaptive trust model that can deal with the requirements of each class of applications. Therefore, we have presented well-defined criteria to point out the key issues of the existing studies and to set up some insights for research within this scope.
Keywords: VANET; security; trust management; attacks; reputation; similarity; behavior; utility.
Multi-constraint Zigbee Routing to Prolong Lifetime of Mobile Wireless Sensor Networks
by Chhagan Lal, Pallavi Kaliyar, Chotmal Choudhary
Abstract: Due to the recent developments in hardware technology and deployment techniques, Mobile Wireless Sensor Networks (MWSNs) are attracting a large array of real-world applications. However, practical realization of these applications is still constrained due to inherent characteristics of MWSNs such as highly dynamic topology, low bandwidth, and finite energy of nodes. These characteristics causes threat to MWSNs basic functionalities, which includes network formation, self-organization, route discovery, and communication management. Hence, improving the lifetime of MWSNs, and minimizing the mobility induced route breaks are the key issues in MWSNs. Zigbee is an advanced technology that works on IEEE standard 802.15.4 and it is suitable for contrainted networks such as MWSNs as well. The main features of Zigbee such as low energy and network bandwidth consumption, and lower deployment cost greatly helps to prolong network lifetime in MWSNs. To this end, in this paper, we propose a multi-constraint Zigbee based Reactive Routing (MZRR) protocol for MWSNs to prolong the network lifetime. Our MZRR protocol uses node energy and hop-to-hop transmission efficiency along with network mobility as metrics during its route discovery process to discover highest remaining lifetime routes. MZRR protocol ensures that the discovered routes has high transmission efficiency which leads to low energy and link bandwidth consumption in the network. By keeping the energy utilization of sensors balanced, MZRR protocol avoids the dead zones in the surveillance areas, this could be very important in data-critical applications. We fully implement MZRR protocol on NS-3 simulator, and the results obtained are compared with traditional AODV and state-of-the-art routing algorithms in terms of relevant parameters such as energy consumption, end-to-end delay, packet delivery ratio, network life-time and network routing overhead.
Keywords: Wireless Sensor Network; Zigbee; Energy Efficiency; Network Mobility; Link Lifetime; IEEE 802.15.4.
Reliable Sense Maintenance Scheme by Sense Holes Recognized and Self-healing in Sensor Networks of Internet of Things
by J.U.N. LIU, Xu Lu, Tao Wang
Abstract: Sense holes recognized and repaired in sensor networks have important significance for sense performance. Most of the existing researches are based on the assumption that the sensor can provide the location or other ideal condition. In this paper, a distributed reliable sense maintenance scheme by sense holes recognized and self-healing was presented. Firstly, it reduced the required nodes density limit to maintain a reliable sense by mathematical analysis. Then, sense holes recognized algorithm based on the Hamiltonian graph and computation geometry was proposed in this paper. It could identify triangular holes and realize a good recognition rate without an accurate position. Based on virtual forces strategy, sense holes self-healing algorithm was presented. Simulation results showed the algorithm was superior to others in energy-balancing. The sense holes recognized algorithm could efficiently and quickly detect sense holes in sensor networks as shown in simulations.
Keywords: Sensor networks; Sense hole recognized; Self-healing; Nodes deployment.
Application of Congestion Avoidance Mechanism in Multimedia Transmission over Mesh Networks
by Biaokai Zhu, Jumin Zhao, Deng-ao Li, Ruiqin Bai
Abstract: The unreliable nature and shared multi-media of multi-hop communications cause the deployment of multi-media applications in wireless mesh network a thorny problem. For instance, video is usually compressed into a group of frames before transmission, resulting in unrecoverable destruction during the display process. The importance of different frames' type is quite different. However, they are considered as same in most existing wireless mesh networks. In this paper, we propose a novel Congestion Avoidance Mechanism for multimedia transmission over 802.11e mesh networks. In our mechanism, we added priority for video packets. According to the significance of frames, we proposed an adaptive mechanism involves the mapping of H.264 video packets to appropriate access categories in IEEE 802.11e standard. Simulation results show that our mechanism improves Quality of Service (QoS) of multimedia transmission.rn
Keywords: Multimedia transmission; 802.11e; wireless mesh network.
Efficient Data Dissemination Approach For QoS Enhancement in VANETs
by Sachin Khurana, Gaurav Tejpal, Sonal Sharma
Abstract: Vehicular ad hoc networks (VANETs) have seen tremendous growth in the last decade, providing a vast range of applications in both military and civilian activities. The temporary connectivity in the vehicles can also increase the driver's capability on the road. However, such applications require heavy data packets to be shared on the same spectrum without the requirement of excessive radios. Thus, efficient approaches are required which can provide improved data dissemination along with the better quality of services to allow heavy traffic to be easily shared between the vehicles. In this paper, an efficient data dissemination approach is proposed which not only improves the vehicle to vehicle connectivity but also improves the QoS between the source and the destination. The proposed approach is analyzed and compared with the existing state-of-the-art approaches. The effectiveness of the proposed approach is demonstrated in terms of the significant gains attained in the parameters namely, end to end delay, packet delivery ratio, route acquisition time, throughput, and message dissemination rate in comparison with the existing approaches.
Keywords: VANETs; delay; QoS; Data Dissemination; Fuzzy sets.
A Challenge-Response Mechanism for Securing Online Social Networks against Social Bots
by Mohamed Torky, Ali Meligy, Hani Ibrahim
Abstract: Social bots is fast becoming a serious security threat to Online Social Networks (OSNs). Social bots are automated software tools able to execute malicious activities in OSNs systems in an automated fashion. It can perform auto-sharing and posting, sending fake friend requests, harvesting private information, etc. There is evidence that social bots play a crucial role in penetrating privacy and security of social networks. Hence, these malicious software tools represent a big security challenge against Social Network Service Provider (SNSP). In this paper, we introduce a novel anti-bot mechanism called Necklace CAPTCHA for securing OSNs platforms against the automated behaviors of social bots. Necklace CAPTCHA is an Image-based CAPTCHA, which utilizes the functionality of Necklace Graph approach to generate its challenge-response tests in a novel fashion. The results demonstrated that Necklace CAPTCHA is an effective and secure anti-bot mechanism compared with other CAPTCHAs in the literature with respect to the usability and security metrics.
Keywords: Online Social Networks (OSNs); Security and Privacy; System Usability; Social Bots ; CAPTCHA; Necklace Graph.
Design of a Monitoring and Safety System for Underground Mines Using Wireless Sensor Networks
by Coert Jordaan, Reza Malekian
Abstract: A mine safety system using a wireless sensor network is implemented. Sensor nodes and a monitoring system are developed to be used in the underground mining environments. Investigations are done into sensor design for underground mines, as well as the use of sensors to profile the underground mining environment and the use of wireless communication in the underground mining environment. The information is used to design and implement a robust hardware-based sensor node with standalone microcontrollers that sample data from six different sensors, namely temperature, humidity, airflow speed, noise, dust and gas level sensors, and transmit the processed data to a graphical user interface, developed using Qt Creator. The system reliability and accuracy is tested in a simulated mine. The wireless mine profiling sensor node, with its monitoring software and receiver unit was successfully implemented. It provided linear and accurate results over nearly a month of daily testing in the simulated mine. It is observed that critical success factors for the wireless sensor node is its robust design, which does not easily fail or degrade in performance. The node also has strong, self-adaptive networking functionality, to recover in the case of a node failure.
Keywords: Mine safety system; wireless sensors; temperature sensor; humidity sensor; airflow speed sensor; noise sensor; dust sensor; gas sensor; error detection.
Signal Technique for Friend or Foe Detection of Intelligent Malicious User in Cognitive Radio Network
by Saifur Rahman Sabuj, Masanori Hamamura
Abstract: To address spectrum scarcity, cognitive radio networks have been proposed as a means to improve spectrum utilization and effciency. In regulation policy for cognitive radio networks, unlicensed users (secondary users) are allowed to utilize unoccupied spectrum when it is not being used by licensed users (primary users). In point of fact, security issues arise when intelligent malicious users can attack cognitive radio networks and decrease the permitted channel for secondary users. In this paper, we propose a novel scheme, based on friend or foe (FoF) detection technique with physical layer network coding, to enable discrimination between secondary users and intelligent malicious users. Theoretical expressions are derived for probabilities of detection of secondary user, miss detection, and false alarm. In addition, the effectiveness of the proposed approach is evaluated by theoretical analysis and Monte Carlo simulation. Furthermore, an algorithm is proposed for distinguishing between secondary user and intelligent malicious user. Finally, based on the outcome of simulation of probabilities and normalized cross- correlation, it is determined that the proposed scheme outperforms in terms of OFDM signal compared with QPSK signal over cognitive radio network.
Keywords: Cognitive radio network; Friend or foe detection; Physical-layer network coding; Cross-correlation.
Designing Secure and Reliable Mobile Agent Based System for Reliable MANET
by Moumita Roy, Chandreyee Chowdhury, Munshi Navid Anjum, Sarmistha Neogy
Abstract: Mobile Adhoc NETwork (MANET) provides a promising platform for pervasive computing applications. Mobile agents are found to be effective for executing such pervasive computing applications. The motivations behind this are advancement in technology, wireless networking, sensor network, ambient intelligence etc. However, since MANET is inherently more vulnerable to security threats and prone to topology changes, reliability and security issues must be addressed before mobile agents are commercially deployed. There are few works on securing mobile agents but even fewer focuses on MANET. This work is our attempt to design a lightweight trust based reputation scheme to protect the agents against network layer threats. The scheme is based on Dempster-Shafer belief theory. Performance of the trust based reputation scheme with respect to network and system reliability is analyzed. The work is simulated and the results show that even for a fairly hostile MANET, the effective reliability of distributed application can be increased using mobile agent based system.
Keywords: Reputation; Trust; Demster-Shafer Belief Theory; Reliability; Monte Carlo Simulation.
Energy Efficient Hierarchical Multi-Path Routing Protocol to Alleviate Congestion in WSN
by Sunitha GP, Dilip Kumar S M, Vijay Kumar B P
Abstract: Congestion easily occurs in wireless sensor networks (WSN) due to it's centralized traffic pattern. It has a negative impact on the network performance in terms of decreasing throughput and increasing energy consumption. %In WSN, the main concern is to control congestionrnIn order to achieve high energy efficiency, network longevity, better fairness and quality of service, it is important to detect congestion in (WSN) in a timely manner. In this paper, an energy efficient hierarchical multi-path routing protocol to alleviate congestion and energy balancing problems is proposed.rn The algorithm is designed by partitioning the network into equal sized zones to achieve complete network connectivity and to reduce packet transmissions. The zone leaders ((ZL's)) selected are shifted on different nodes on network dynamic conditions to avoid hotspots and to provide energy balancing. For efficient data transmission quicker and optimal multiple paths are established using merged zone and Hierarchical network ((HiNet)) topology structure. The proposed algorithm detects the congestion by monitoring the path quality. The detected congestion is a result of overloaded links or nodes on the path. In addition, the algorithm proactively controls the congestion by dynamically shifting the transmission paths on their quality and alleviate it reactively using traffic splitting approach. The goal of this approach is to control resources instead of controlling the network load. The simulation results demonstrate that the proposed algorithm performs better as compared to other congestion control algorithms in terms of throughput, energy consumption and packet delivery ratio in a resource constraint wireless sensor network
Keywords: Congestion control; Multi-path routing; Energy efficiency; Load balancing; WSN.
A Novel Faster Failure Detection Strategy for Link Connectivity using Hello Messaging in Mobile Ad Hoc Networks
by Alamgir Naushad, Ghulam Abbas, Ziaul Haq Abbas, Lei Jiao
Abstract: Faster failure detection is one of the main steps responsible for efficient link connectivity in mobile ad hoc networks (MANETs). Under a random behavior of network nodes and link/node failure, there must be a unified approach to describe an adequate Hello messaging strategy for link connectivity in MANETs. In order to tackle this issue, we present a strategy for achieving faster failure detection, and derive algorithmic attributes of the proposed strategy on the basis of multiple parameters of interest after modelling it as a Markov process. We also present novel algorithms to minimize the biggest chunk of delay incurred as a result of link re-connectivity and, thus, improve network connectivity in MANETs. Simulation and analytical results indicate efficacy of the proposed strategy in achieving faster failure detection and efficient link re-connectivity.
Keywords: Faster failure detection; Hello messages; MANETs; Stochastic processes; Link connectivity.
Mitigating SSDF Attack using Distance-based Outlier approach in Cognitive Radio Networks
by Wangjam Niranjan Singh, Ningrinla Marchang, Amar Taggu
Abstract: Collaborative spectrum sensing is employed in cognitive radio networks for improving the spectrum sensing accuracy. The collaborating cognitive radios send their individual sensing results to the fusion center (FC) which aggregates the results to come to a final sensing decision. Malicious radios may adversely influence the final sensing decision by transmitting false spectrum sensing results to the FC. This attack is commonly known as the spectrum sensing data falsification (SSDF) attack. Hence, in the light of such a threat, it is pertinent for the FC to identify any such malicious radios, if any and isolate them from the decision process. In this paper, a distance-based outlier detection approach is proposed which mines the sensing reports at the FC for detection and isolation of such malicious users. Numerical simulations results support the validity of the proposed approach.
Keywords: SSDF attack; distance-based outlier detection; cognitive radio network; data mining.
IOT Enabled Adaptive Clustering based Energy Efficient Routing Protocol For Wireless Sensor Networks
by Muhammad Asad, Aslam Hayat, Yao Nianmin, Naeem Ayoub, Khalid Ibrahim Qureshi, Ehsan Ullah Munir
Abstract: Wireless Sensor Networks (WSNs) consists of hundreds and thousands of micro-sensor nodes which are distributed in the sensing field to sense the uncertain events. These sensor nodes plays an important role in Internet of Things (IoT). Energy consumption has been a major issue in WSNs, various energy efficient conventional routing protocols are proposed to minimize the communication energy cost of sensor nodes. In IoT enabled WSNs, these sensor nodes are resource controlled in various ways, such as energy, storage, computing, communication and so on. In conventional routing protocols clustering technique is performing superiorly but due to the limited characteristics, suggested routing protocols are not as much smart and flexible to generate a perfect Cluster-Head (CH) because these routing protocols are limited to centralized and distributed or homogeneous and heterogeneous networks. In this paper, we propose a new IoT enabled Multi Adaptive Clustering (MAC) energy efficient routing protocol for WSNs to minimize the energy dissipation and improve the network performance. This new technique holds the hybrid cluster formation algorithm in which the network topology is divided into two regions the first region is centralized and the second region is distributed. Both regions contains homogeneous and heterogeneous nodes while the sink is static and located in the center of both networks. Specifically, proposed IoT enabled MAC routing protocol holds the major three properties: Enabling of resources to sensor nodes through IoT, hybrid cluster formation to distribute the network load evenly among sensor nodes and a new mechanism to minimize the energy consumption in long range data transmission. Our simulation results give significant proof that MAC performs better than state-of-the-art routing protocols such as LEACH-C, DEEC, D-DEEC and E-DEEC. In addition, performance evaluation proofs that MAC is suitable for the network which requires longer network lifetime.
Keywords: Internet of Things; Wireless Sensor Networks; Energy Efficient; Routing Protocols.
A new approach for the recognition of human activities
by SALIMA SABRI, AlOUI Abdelouhab
Abstract: The evaluation of a patient\'s functional ability to perform daily living activities is an essential part of nursing and a powerful predictor of a patient\'s morbidity, especially for the elderly. In this article, we describe the use of a machine learning approach to address the task of recognizing activity in a smart home.We evaluate our approach by comparing it to aMarkov statistical approach and using several performance measures over three datasets. We show how our model achieves signicantly better recognition performance on certain data sets and with different representations and discretisation methods with an accuracy measurement that exceeds 92%and accuracy of 68%. The experiments also showa signicant improvement in the learning time which does not exceed one second in the totality of the experiments reducing the complexity of the approach.
Keywords: Ubiquitous applications; automatic learning; Katz ADL; activity recognition; probabilistic models; wireless sensor network.
A Novel Method for Time Delay Prediction in Networked Control Systems
by Pei XU, Jianguo WU
Abstract: Time delay prediction is a crucial issue of networked control systems. Previous methods mainly use individual model to predict time delay, which causes the limitation that the proposed model can only be suitable applied to either linear or nonlinear data. This paper proposed a novel method to predict time delay in networked control systems which considers several different individual models as the component models to form a combined model and takes full advantages of these component models. By applying Lagrange multiplier method to minimize prediction error, the proposed OW (optimal weight) algorithm is able to calculate the proper weight coefficients of component models in order to improve the prediction performance. Compared with the existing methods, the proposed combined model can improve the prediction accuracy and support robustness, variability and scalability. The simulation experiments verify the effectiveness of the proposed method.
Keywords: networked control systems; time delay prediction; RBF neural network; ARMA model; optimal weight; combined model.
A reputation-based truthfulness paradigm for multi-hop transmission in cognitive radio networks
by Trupil Limbasiya, Debasis Das, Ramnarayan Yadav
Abstract: Cognitive radio networks (CRNs) consist of numerous intellectual users with the capability of sensing and sharing underutilized spectrum, and they are called as cognitive users (CUs). The spectrum is allocated to licensed users or primary users (PUs) but, generally, they do not utilize it completely. To overcome the ever-increasing spectrum demand and utilize the underutilized licensed spectrum, the cognitive radio plays a major role. In this distributed environment, the communication among CUs becomes more challenging due to channel heterogeneity, uncontrolled environment, a need of cooperative sensing for accurate sensing result, etc. Additionally, there are different attacks, e.g., primary user emulation (PUE), control channel saturation DoS (CCSD), selfish channel negotiation (SCN), spectrum sensing data falsification (SSDF), modification, and man-in-the-middle. Then, this affects and degrades system and CRN performance, which creates an opportunity for a trust management model to manage the CRNs properly. In this paper, we propose an efficient trust management protocol for centralized and distributed CRNs that are to build a trust-based system over the complete cognitive cycle to protect against security attacks brought by the unreliable individuals. To address the security issues, a clustering scheme is used in the distributed environment for effective cooperation among CUs. The security analysis and simulation results represent that the proposed protocol can identify malicious behavior and enhance fairness and powerfulness of the network in centralized and distributed circumstances.
Keywords: Attacks; Cognitive radio networks; Integrity; Trust management.
Throughput of Cooperative HARQ protocols for Underlay Cognitive Radio Networks using Adaptive and Fixed Transmit Power
by Nadhir Ben Halima, Hatem Boujemaa
Abstract: In this paper, we study theoretically and by simulations the throughput of cooperative Hybrid Automatic Repeat reQuest protocolsrnfor underlay cognitive radio networks. Both fixed and adaptive power transmission are studied. Different relay selection techniques with Amplify and Forward (AF) and Decode and Forward (DF) relaying are investigated.rnFor fixed transmit power, some relays are not available since they generate an interference to primary receiver larger than a predefined value T.rnThe best relay is selected among the available ones.rnFor adaptive transmit power, all relays adapt their power so that interference to primary receiver is always lower than a predefined threshold $T$. In this case, all relays will be available for retransmitting the secondary source packet.rnBoth Average Interference Power (AIP) and Peak Interference Power Constraints (PIP) are studied. We also analyze the effect of primary interference on secondary throughput.
Keywords: Cognitive Radio Networks; HARQ.
GOOSE: Goal Oriented Orchestration for Smart Environments
by Vincenzo Catania, Gaetano La Delfa, Giuseppe La Torre, Salvatore Monteleone, Davide Patti, Daniela Ventura
Abstract: Smart environment scenarios are characterized by the presence of users, with different needs and preferences, and everyday life objects exploited to meet the expectations of users themselves. Connecting objects to the Internet and making them accessible from remote is not sufficient to make an environment "smart" since such ecosystems should also be able to enable context-sensitive actions along with a management of the interaction between objects and users. In this work, we propose GOOSE, a platform which aimed at interpreting users goals expressed in natural language in order to generate, select, and safely enforce a set of plans to be executed to fulfill target goals. After highlighting the main challenges affecting typical Machine to Machine (M2M) communication scenarios, we show how the use of a semantic reasoner can be used to allow the composition of plans consisting of sequences of services to be called on the smart environment objects. Finally, we address the issue of secure communications between platform and objects, and the management of potentially inconsistent goals.
Keywords: Machine to Machine; RESTful services; Goal-oriented Architecture; User-object interactions; Semantic descriptions; Indoor localization;.
Radio Characteristics and Mobility based Routing for Multimedia Services over MANETs
by Lokesh Sharma, Chhagan Lal
Abstract: Providing an adequate level of Quality-of-Experience (QoE) for multimedia applications in Mobile Ad-hoc Networks (MANETs) is a challenging task due to its environmental characteristics, such as dynamic network topology, variable bit-rates of transmitting traffic, and fluctuating link conditions. In this paper, we propose a QoS-aware Radio Characteristics and Network Mobility (Q-RCNM) based routing protocol, and its multipath variant (i.e., Q-RCNMM). Our protocols ensure adequate QoE to the end users while receiving the multimedia traffic. Q-RCNM uses link-bandwidth, link-delay, and link-transmission efficiency ratio as QoS metrics along with the node mobility during its QoS-aware route discovery phase. We propose novel techniques for accurately estimating the aforementioned QoS metrics. Additionally, we design a joint analytical model that simultaneously considers the dynamic values of the aforementioned metrics to generate a single link-QoS value. Simulation results in terms of Peak Signal-to-Noise Ratio (PSNR), delay, route throughput, transmission efficiency, and route lifetime, shows the efficiency of our proposal when compared with similar state-of-the-art techniques.
Keywords: Link stability; Emulation; Bi-directional link loss factor; Video streaming; QoS-aware routing; Quality of Experience; Cross–layer communication.
Type-2 Fuzzy Logic based Energy-Efficient Transceiver Resource Schedule in Multi-radio WSNs
by Wei Peng, Dongyan Chen, Wenhui Sun
Abstract: Inspired by the type-2 fuzzy logic (T2FL), the energy-efficient radio resource schedule mechanism is proposed to deal with the multi-radio resources management problem in MRWSNs. Firstly, three important models, including channel quality estimation model, radio energy dissipation model and residual energy model, are established and analyzed. Then using the three important factors as the input variables, the selection probability of each transceiver as output variable, the T2FL based energy-efficient radio resource schedule scheme is designed. Moreover, both experimental and simulation results indicate that the proposed schedule mechanism can effectively improve the network performance, such as throughput, energy efficiency, the success rate of data transmission etc.
Keywords: multi radio resource; wireless sensor network; type-2 fuzzy; energy-efficient; transceiver schedule.
Data gathering maximization for wireless sensor networks with a mobile sink
by Zongyuan Han, Tianyun Shi, Xiaojun Lv, Xinchun Jia, Zhongying Wang, Dong Zhou
Abstract: Recent studies have demonstrated that the significant benefit can be achieved by using mobile sinks for data gathering in wireless sensor networks (WSNs). However, most of them employed a typical scheme that the mobile collector pauses at the anchor points on its moving tour for a period time to collect the data from nearby sensors. In this paper, the data gathering process is divided into two stages named parking communication (PC) and moving communication (MC). We focus on maximizing the total amount of data gathering by the mobile sink, and formulate the problem as two different optimization models under several constraints for these two different communication stages. Accordingly, dual decomposition and simplex methods are dexterously exploited to derive the optimal communication time and flow rates allocation schemes. Computational results demonstrate the efficiency of the proposed algorithms.
Keywords: Wireless sensor networks; Mobile data gathering; dual decomposition; nonlinear programming.
A Multi-channel Distributed Routing Scheme for Smart Grid Real-time Critical Event Monitoring Applications in the Perspective of Industry 4.0
by Muhammad Faheem, Rizwan Aslam But, Basit Raza, Md Asri Bin Ngadi, Cagri Gungor
Abstract: Recently, the 4th industrial revolution known as Industry 4.0 has paved way for a systematical deployment of the modernized power grid to fulfill the continuously growing energy demand of the 21st century. This industrial revolution in the power sector is known as the smart grid industry (SGI) 4.0. In SGI 4.0, the industrial wireless sensor network (IWSN) and the internet of things (IoT) are envisioned as key promising communication technologies for monitoring various SG applications. In addition, the ubiquitous computing using these communication technologies connects various smart grid devices to carry out monitoring and control logic intelligently from any remote location, worldwide. However, the highly dynamic nature of the SG environments brings several unique challenges to their reliable communication in the smart grid. As a result, the quality of service (QoS) communication is hampering for cognitive radio sensor networks (CRSNs)-based SG applications. Thus, a sophisticated, reliable and QoS-aware multi-hop communications network architecture enabling a real-time exchange of data for various CRSNs-based applications is essential in the SGI 4.0. Hence, this paper proposes a novel channel-aware distributed routing protocol named CARP for CRSNs-based SG applications. In CARP, the proposed cooperative channel assignment mechanism significantly improves the detection reliability and mitigates the noise and congested spectrum bands resulting in reliable and high capacity links for CRSNs-based SG applications. Moreover, to support higher capacity data requirements and to maximize the spectrum utilization, the proposed multi-hop routing mechanism selects a secondary user relay node rich in spectrum information with longer ideal probability at low interference in the network. The extensive simulation results conducted through EstiNet9.0 reveal that the proposed scheme achieves its defined goals compared to existing routing schemes designed for CRSNs-based applications.
Keywords: Industry 4.0; Smart grid; Cognitive radio; Internet of thing; Wireless sensor networks.
Embedded Systems Codesign under Artificial Intelligence perspective: a review
by Fateh Boutekkouk
Abstract: Intelligent Embedded Systems (IES) and their distributed versions, represent a novel and promising generation of embedded systems. IES have the capacity of reasoning about their external environments and adapt their behavior accordingly. Such systems are situated in the intersection of two different branches that are the embedded computing and the intelligent computing. On the other hand, intelligent embedded software (IESo) is becoming a large part of the engineering cost of intelligent embedded systems. IESo can include some Artificial Intelligence-based systems such as expert systems, neural networks and other sophisticated Artificial Intelligence (AI) models to guarantee some important characteristics such as self-learning, self-optimizing and self-adaptation. Despite, the wide spread of such systems, some design challenging issues are arising. Designing a resource constrained software and at the same time intelligent is not a trivial task especially in a real time context. To deal with this dilemma, embedded systems researchers have profited from the progress in Semiconductor technology to develop specific hardware to support well AI models and render the integration of AI with the embedded world a reality.
Keywords: embedded systems; Codesign; Artificial Intelligence; Intelligent Embedded Systems.
Enhancing the Dependability of Wireless Sensor Networks under Flooding Attack: A Machine Learning Perspective
by Jasminder Kaur Sandhu, Anil Kumar Verma, Prashant Singh Rana
Abstract: Wireless Sensor Networks (WSNs) are gaining paramount importance due to its application in real-time monitoring of geographical regions. Its deployment paradigm encompasses myriad of applications in terrestrial, underground and underwater WSNs. Nowadays the paradigm shift is taking place from mobile computing to Internet of Things. Bridging the two technologies result in the development of new applications with security as an essential feature. The discussion of applications without incorporating dependability and security features would be incompetent in a hostile environment. Extensive features such as traffic monitoring, proper resource utilization, security must be added to networks to assure quality transmission of data and enhance dependability. Security deals with detection and mitigation of various attacks. In flooding attack, an attacker repeatedly sends packets at higher rates, thereby causing packet drop and exhaustion of the link capacity. Thus, any further legitimate communication is ignored. To protect the network against the flooding attack, an Intrusion Detection System based on novel randomized and normalized deployment approach is proposed. We have found that Machine Learning models play a significant role in the prediction of Data Flow in WSNs. Network simulator is used to generate the dataset and Machine Learning techniques are used to enhance the dependability against flooding attack.
Keywords: Wireless Sensor Networks; Dependability; Machine Learning; Data Flow; Flooding.
H-LPS: A Hybrid Approach for Users Location Privacy in Location Based Services
by Sonia Sabir, Inayat Ali, Eraj Khan
Abstract: Applications providing Location-Based Services (LBS) have gained much attention and importance with the notion of the Internet of Things (IoT). Users are utilizing LBS by providing their location information to third-party service providers. However, location data is very sensitive that can reveal users private life to adversaries. The passive and pervasive data collection in IoT upsurges serious issues of location privacy. Privacy-preserving location-based services is a hot research topic. Many anonymization and obfuscation techniques have proposed to overcome location privacy issue. In this paper, we have proposed a Hybrid Location Privacy Scheme (H-LPS), a hybrid scheme mainly based on obfuscation and collaboration for protecting users location privacy while using location-based services. Obfuscation naturally degrades the quality of service, but provides more privacy as compared to anonymization. Our proposed scheme, H-LPS, provides a very high level privacy yet providing a good accuracy for most of the users. Privacy level and service accuracy of H-LPS is compared with state of the art location privacy schemes and it is showed that H-LPS could be a candidate solution for preserving users location privacy in location based services.rn
Keywords: Location privacy; Location Based Services; Obfuscation; Anonymization; Mobile location privacy.
Secure and remote firmware update of cellular IoT micro devices with limited resources
by Ahmet Cezayirli
Abstract: Typically, cellular IoT (Internet of Things) devices are spread over very large areas, usually countrywide or even worldwide. This makes the firmware update operation a troublesome and costly task, and it is usually avoided as long as possible. However, due to some bugs detected in the core software and/or some significant performance enhancements developed after the release of the device, the need for a firmware update becomes inevitable. We propose a new methodology in order to fulfil the firmware update remotely in an easy and secure way for especially the devices with quite limited resources, such as very small RAM and low processing power. We utilize MMS (Multimedia Messaging Service) functions, and send the firmware to the remote cellular IoT devices as encrypted attachment. The preparation steps of the attachment are explained in detail, a handshaking mechanism is established and all are tested on a particular hardware. Some important remarks are also provided, so that major practical aspects of the methodology would be readily available in implementing it on hardware/software architectures of new IoT devices.
Keywords: Firmware update; cellular IoT; remote device; MMS attachment; code encryption.
Using ubiquitous data to improve smartwatches context awareness: A case study applied to develop wearable products
by Qing-Xing Qu, Yuankun Song
Abstract: Most recently, a large amount of data is being generated by various applications on smart devices, which could contain abundant information related to the users daily lives. This study aims to investigate whether the use of ubiquitous data could effectively improve smartwatches context awareness. A prototype of a context-aware system consisting of an Android application and a web application was developed, and an experiment in which 20 participants were recruited to complete several tasks with a smartwatch was conducted. The results showed that the smartwatch with the prototype application successfully decreased the effort cost (operations), task completion time, and error rate by making use of ubiquitous data to capture users real-time contexts and automatically execute corresponding operations. Moreover, users with a proposed context-aware system could have better user experience and more positive affective responses than the non context-aware system. Furthermore, findings in this study could give a better understanding and suggestions to designers when they intend to design a new smartwatch or improve an existing application on a smartwatch with the use of ubiquitous data.
Keywords: Ubiquitous data; Context awareness; Smartwatch; Location-based service; Context-aware recommendation system; Ubiquitous computing.
Incentive Mechanism based Influential Maximization Scheme for Social Cloud Service Networks
by Sungwook Kim
Abstract: An effective interaction between the Social Network Services (SNS) and Cloud Computing (CC) enables the connection of people to the ubiquitous computing universe. The integration of SNS and CC is a technological revolution that presents the future of connectivity and reachability. This paper explores the novel paradigm for future Internet of Things (IoT). Although there have been some studies in social-driven IoT, they merely consider the CC technique to improve service qualities and influences. In this study, we develop a novel social cloud control scheme based on the Incentive Mechanism (IM) approach. To maximize the total SNS system performance, SNSs have been adaptively executed in the CC system while taking into account the social welfare. In addition, we protect each users privacy according to the Differential Privacy (DP) method. Therefore, our study can capture the properties of SNS and CC, and provides an effective solution for the social cloud system while ensuring privacy. Finally, we have conducted extensive simulations. The experimental results demonstrate the efficiency and effectiveness of the proposed scheme for the real world social cloud services. The main contribution of our work lies in the fact that we shed some new light on the relationship among SNS, CC and privacy for the future social cloud system. To the best of our knowledge, there is few previous work about this issue.
Keywords: Social network services; Social cloud computing; Influential maximization; Incentive mechanism; Differential privacy.
Base Station Assisted Relay Selection in Device-to-Device Communications
by Ushik Shrestha Khwakhali, Prapun Suksompong, Steven Gordon
Abstract: The performance of cooperative cellular networks can be enhanced by using social information of users in the network. This paper presents a social-aware midpoint relay selection scheme that increases average throughput of D2D communication between users in the network leveraging social trust among nodes while selecting a relay node. The selection of a relay node is such that it has strong social link with the source and also located near to the midpoint of the distance between the source and the destination. Calculation of average throughput via simulation shows that our proposed scheme outperforms existing hybrid relay selection scheme by Pan and Wang by upto 14%. In addition, our proposed introduction of probe limit and wise selection of social threshold value can further enhance the throughput when social trust among nodes are high.
Keywords: Cooperative networks; device-to-device (D2D) communications; social networks; social-aware relay selection; data rate; throughput.
Cost Efficient Hybrid Techniques for DSM in Smart Homes
by Rasool Bukhsh, Nadeem Javaid, Majid Iqbal Khan, Zahoor Ali Khan, Imran Usman
Abstract: In smart grid, the minimum cost for power consumption is attained by scheduling the appliances load. Shifting the appliances load from on-peak to off-peak time reduces the cost in users bill without compromising the load demand. In this paper, four scheduling algorithms are proposed by hybridizing Elephant Herding Optimization (EHO) with genetic, firefly, bacterial foraging and binary particle swarm optimization algorithms. Extensive simulations are performed to schedule the home appliances using proposed algorithms with three pricing tariffs: day ahead real time pricing, inclined block rates and critical peak pricing. The cost efficiency of optimized power consumption is analyzed. Results show that more cost is reduced with proposed hybrid algorithms as compared to the unscheduled and state-of-the-art algorithms.
Keywords: Smart Meter; Smart Home; Operation Time Interval; Cost Efficiency; Appliances Schedule.
Prefetching and Caching Schemes for IoT Data in Hierarchical Edge Computing Architecture
by Tzu-Jung Chen, Jang Ping Sheu, Yung Ching Kuo
Abstract: With the growing number of the Internet of Things (IoTs) devices and mobile devices, the data traffic produced by these devices causes high network load, and these devices endure long access latencies to communicate with the cloud. The emergence of Edge Computing, caching and prefetching at the edge of the networks are promising solutions to these problems. Therefore, we propose caching and prefetching schemes for the Internet of Things data based on a four-tier hierarchical Edge Computing architecture, and our goal is to reduce data access latency. In our architecture, caches are deployed at 1st- and 2nd-tier edge nodes and the caching scheme is designed especially for the IoTs data. We analyze the relations of all users access requests and prefetch popular data among all users to the cache based on the predictions of user preferences. The experimental results show that the proposed schemes can effectively reduce user access latencies. Comparing with the average latencies under Cloud Computing architecture, the rate of improvement is up to 95%.
Keywords: cache; edge computing; association rule mining; Internet of Things; prefetching.
A Note on Cloud Computing Security
by Deepak Garg, Jagpreet Sidhu
Abstract: Cloud computing has become an emerging technology which has huge impact. Existing security algorithms cannot meet the needs of cloud computing users as security issues have become increasingly prominent, becoming an important factor restricting the development of cloud computing. Reports reveals that organizations have experienced various attacks in past year. Research community has immensely focused on developing and optimizing security techniques to overcome this hurdle in cloud. Due to huge literature it becomes difficult to comprehend overall structure and advancements. This domain needs an analytic approach to completely understand the problem domain that is why this article represents same in specific context of security. Further a notion on security issues in cloud computing with respect to vulnerabilities, threats and attacks is discussed. Paper also proposed two research evaluation parameters that are effective citation and effective impact factor for better appreciation. Article also analyses patterns, trends and other factors for directing research activities. Finally, a global research trends on security domain are evaluated and analysed.
Keywords: Cloud Computing; Security; Survey; Effective Citation (EC); Effective Impact Factor (EIF); Vulnerabilities; Threats; Attacks.
Activity Recognition Approach based on Spatial-Temporal constraints for Aged-care in Smart Home
by Haibao Chen, Shenghui Zhao, Cuijuan Shang, Guilin Chen, Chih-Yung Chang
Abstract: Activity recognition plays an important role in smart homes for aged-care. In this paper, we formulate the problem of activity recognition and propose a new method based on spatial-temporal constraints to carry out activity recognition, which consists of five phases: Initialization, Segmentation, Sensor Data Representation, Activity Exploration as well as Activity Identification. Besides, we analyze the time complexity and space complexity of our approach in theory.To evaluate our approach, we carried out experiments on real dataset from Wireless & Mobile Network Laboratory, Tamkang University. The experimental results demonstrate an improvement of 5.6% in the accuracy on average of recognized activities in comparison to the method of support vector machine (SVM).
Keywords: Activity recognition; smart home; wireless sensor network;Aged-care.
A Novel Reliability based High Performance Decoding Algorithm for Short Block Length Turbo Codes
by Salija P, B. Yamuna, T.R. Padmanabhan, Deepak Mishra
Abstract: Satellite communication applications use Turbo codes as the standard error correcting code due to its Shannons capacity approaching performance. However short block length Turbo codes exhibit significant performance degradation. This is a limiting factor in applications like transmissions over the telecommand links for satellite communications that involve the use of short length Turbo codes. A novel reliability based Turbo decoding algorithm that addresses the performance improvement of short block length Turbo codes, is being proposed in this paper. Simulation results show a coding gain of 2.45 dB at BER of 10-3 for short length codewords. The proposed decoding algorithm has low computational complexity compared to the conventional iterative decoding algorithm. The relatively lower computational complexity and the conspicuous improvement in BER performance make the method quite attractive.
Keywords: Reliability; Turbo codes; Bit Error Rate; Decoding.
An adaptive data rate algorithm for improving energy eciency for multi-gateway LoRaWANs
by LIN-HENG CHANG, Yi Chang, Chih-Kae Guan, Tong-Ying Juang, Wen-Chang Fang
Abstract: The need of the low power, long range, and low cost connectivity for satisfyingrnthe requirement of IoT (Internet of Thing) applications for smart city is leading the emergence of Low Power Wide Area (LPWA) networking technologies. The resource efficiency plays an important role in realistic application, LoRaWAN allows the static end devices to individually adapt and optimize the data rates and the transmission power, which is referred to as Adaptive Data Rate (ADR) problem. In this paper, we develop a new ADR algorithm for multi-gateway LoRaWAN environment to quickly choose the appropriate LoRa transmission parameter for independent LoRa end device based on LoRaWAN specification. To successfully execute the ADR algorithm, we specially rewrite the firmware of Semtech's SX1276 transceivers to implement our proposed ADR algorithm over multi-gateway LoRaWAN system, including end device, multi-gateways and networkrnserver. Our ADR algorithm utilizes the radio link quality, including RSSI, SNR, and packet reception ratio (PRR), from multi-gateways, and the network server determines the appropriate LoRa transmission parameter. Finally, the experimental results illustrate that the proposed algorithm improves the energy efficiency, the effective bit rate, and the battery life of the end-device.
Keywords: LPWA; LoRaWAN; adaptive data rate (ADR); radio link quality; multi-gateways.
A Novel RPL-based Multicast Routing Mechanism for Wireless Sensor Networks
by Ren-Hung Hwang, Min-Chun Peng, Cheng-Yu Wu, Satheesh Abimannan
Abstract: The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) provides the multipoint-to-point, point-to-multipoint, and point-to-point routing mechanisms for wireless sensor networks. However, for point-to-multipoint, i.e., multicast from the sink node, the RPL poses only the principles of routing operation, and the practical mechanism is still an open issue. Two practical routing mechanisms have been proposed in the literature, namely, Multicast Protocol for Low-Power and Lossy Networks (MPL), and Enhanced Stateless Multicast Forwarding with RPL (ESMRF). The MPL aims to be a highly reliable multicast mechanism, but it also incurs serious delays. In contrast, ESMRF establishes simple rules for transmitting multicast packets, however, it lacks reliability. In addition, both mechanisms do not take energy efficiency into consideration. In this paper, we propose a Wireless Shortest Path Heuristic (W-SPH) mechanism for constructing a multicast tree which builds effective routing topology for multicast traffic, and as a consequence, yields higher energy efficiency. We also introduce the Proactive Multicast Forwarding with RPL (PMFR), a multicast mechanism with proactive retransmission and early relay, to increase the reliability of the multicast. Our simulation results demonstrate that the PMFR can achieve a significantly higher delivery ratio and a 50% lower delay than both the MPL and ESMRF. The PMFR also reduces about 40% energy consumption as compared to the MPL. While considering the energy efficiency, that is the energy consumed per successful packet delivery, the PMFR also yields higher energy efficiency than ESMRF in most cases.
Keywords: RPL; Multicast; Wireless Sensor Networks.
Performance Evaluation of Main Approaches for Determining Optimal Number of Clusters in Wireless Sensor Networks
by Meryem Bochra BENMAHDI, Mohamed LEHSAINI
Abstract: Among important issues in the current energy-efficient routing protocols for wireless sensor networks (WSNs) based on clustering approaches are how to determine the optimal number of clusters, how to generate clusters and how select cluster-heads to improve WSNs performance. These approaches aim to reduce energy consumption of the WSN nodes and to extend the network lifetime. This paper reviews and compares the performance of three clustering techniques for determining number of clusters: Rule of Thumb, Elbow, and Silhouette. Each of these techniques involves a distributed K-means approach to generate clusters. Moreover, we compare these three clustering methods with LEACH (Low Energy Adaptive Clustering Hierarchy), Imp_LEACH and MODLEACH in terms of network lifetime, energy consumption and the number of packets sent to the base station (BS). The results obtained indicate that Rule of Thumb method provides better performance compared to other clustering techniques in terms of energy consumption and network lifetime.
Keywords: Clustering; K-means; LEACH; Silhouette; Elbow; Rule of Thumb; WSNs.
Special Issue on: ICSSE 2018 Innovative Services and Emerging Technologies of Smart Cities
by Yo-Ping Huang, Haobijam Basanta, Hung-Chou Kuo, Hsin-Ta Chiao
Abstract: Various technological developments in home-care systems have allowed elderly people to live independently without compromising their safety. A pilot study employing deep learning algorithm was conducted to study the daily routines of elderly people. We monitored unsupervised, diverse daily activities of elderly people such as household chores, sleeping, cooking, cleaning, using the bathroom, watching television, and meditating. The activities were monitored to track humanenvironment interactions by using motion sensors, actuators, and surveillance systems that were mounted inside living rooms, bedrooms, and kitchens and on bathroom doorways to detect safety hazards in the environment for elderly people. Such collected data were used in deep belief networks to ascertain and identify activities that are related to various health and self-care problems. Simulation results show that the proposed system outperforms the support vector machines in terms of F1 score and accuracy in identifying daily activities.
Keywords: sensors; deep belief network; daily activities; abnormal events.
Random Forest, Gradient Boosted Machines and Deep Neural Network for Stock Price Forecasting: A Comparative Analysis on South Korean Companies
by Sanjiban Sekhar Roy, Rohan Chopra, Kun Chang Lee, Concetto Spampinato, Behnam Mohammadi-ivatloo
Abstract: Predicting the final closing price of a stock is a challenging task and even modest improvements in predictive outcome can be very profitable. Many computer-aided techniques based on either machine learning or statistical models have been adopted to estimate price changes in the stock market. One of the major challenges with traditional machine learning models is the feature extraction process. Indeed, extracting relevant features from data and identifying hidden nonlinear relationships without relying on econometric assumptions and human expertise is extremely complex and makes deep learning particularly attractive. In this paper, we propose a deep neural network-based approach to predict if the stock price will increase by 25% for the following year, same quarter or not. We also compare our deep learning method against shallow approaches, random forest and gradient boosted machines. To test the proposed methods, KIS-VALUE database consisting of the Korea Composite Stock Price Index (KOSPI) of companies for the period 2007 to 2015 was considered. All the methods yielded satisfactory performance, namely, deep neural network achieved an AUC of 0.806, random forest, 0.850 and gradient boosted machine, 0.853. Interestingly, deep learning achieved the lowest performance, which although marginal can be explained by the lack of enough training data.
Keywords: Deep neural network; random forest; gradient boosted machine; KOSPI; financial markets.
Task Allocation for Crowd Sensing Based on Submodular Optimization
by Zhiyong Yu, Weiping Zhu, Longkun Guo, Wenzhong Guo, Zhiwen Yu
Abstract: Crowd sensing is becoming a hot topic because of its advantages in the field of smart city. In crowd sensing, task allocation is a primary issue which determines the data quality and the cost of sensing tasks. In this paper, on the basis of the sweep covering theory, a novel coverage metric called t-sweep k-coverage is defined, and two symmetric problems are formulated: Minimize user set under fixed coverage rate constraint (MinP) (MinP) and Maximize coverage rate under user set constraint (MaxC). Then based on their submodular property, two task allocation methods are proposed, namely double greedy (dGreedy) and submodular optimization (SMO). The two methods are compared with the baseline method linear programming (LP) in experiments. The results show that, regardless of the size of the problems, both two methods can obtain the appropriate participant set, and overcoming the shortcomings of linear programming.
Keywords: crowd sensing; task allocation; participant selection; submodular optimization.