Forthcoming articles


International Journal of Sensor Networks


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International Journal of Sensor Networks (52 papers in press)


Regular Issues


  • Recent Advances in Wireless Sensor Networks with Environmental Energy Harvesting
    by Lei Shu, Wanjiun Liao, Jaime Lloret, Lei Wang 
    Keywords: .

  • Does the Assumption of Exponential Arrival Distributions in Wireless Sensor Networks Hold?   Order a copy of this article
    by Krishna Doddapaneni, Ali Tasiran, Enver Ever, Fredrick A. Omondi, Purav Shah, Leonardo Mostarda, Orhan Gemikonakli 
    Abstract: Wireless Sensor Networks have seen a tremendous growth in various applicationrnareas despite prominent performance and availability challenges. One of therncommon configurations to prolong the lifetime and deal with the path loss phenomenarnis having a multi-hop set-up with clusters and cluster heads to relay the information.rnAlthough researchers continue to address these challenges, the type of distributionsrnfor arrivals at the cluster head and intermediary routing nodes is still an interestingrnarea of investigation. The general practice in published works is to compare an empiricalrnexponential arrival distribution of wireless sensor networks with a theoreticalrnexponential distribution in a Q-Q plot diagram. In this paper, we show that such comparisonsrnbased on simple eye checks are not sufficient since, in many cases, incorrectrnconclusions may be drawn from such plots. After estimating the Maximum Likelihoodrnparameters of empirical distributions, we generate theoretical distributionsrnbased on the estimated parameters. By conducting Kolmogorov-Smirnov Test Statisticsrnfor each generated inter-arrival time distributions, we find out, if it is possible tornrepresent the traffic into the cluster head by using theoretical distribution. Empiricalrnexponential arrival distribution assumption of wireless sensor networks holds onlyrnfor a few cases. There are both theoretically known such as Gamma, Log-normalrnand Mixed Log-Normal of arrival distributions and theoretically unknown such asrnnon-Exponential and Mixed cases of arrival in wireless sensor networks. The work isrnfurther extended to understand the effect of delay on inter-arrival time distributionsrnbased on the type of medium access control used in wireless sensor networks.
    Keywords: Wireless Sensor Networks; Performance; Maximum-Likelihood Estimates of Empirical Distributions; Exponential Distribution; Non-Exponential Empirical Distributions; Gamma; Log-normal Distributions; Mixed Log-Normal Distributions;Histograms and Empirical Densities; Q-Q Plots; P-values; Kolmogorov-Smirnov Test Statistics; Theoretical and Empirical Densities and Cumulative Distribution Functions.
    DOI: 10.1504/IJSNET.2016.10001413
  • An Energy Efficient Routing Scheme by using GPS information for Wireless Sensor Networks   Order a copy of this article
    by Byungseok Kang 
    Abstract: A wireless sensor network (or IoT network) is a collection of distributed nodes. These nodes gather data from various sensors and relay that information to a central point through a wireless network. There, the data can be aggregated and have something useful done with it. These types of networks deal primarily with the transmission of small amounts of data that needs to be sent very efficiently. In this paper we propose an energy efficient routing algorithm based on the Global Positioning System (GPS) information. Proposed scheme track the destinations location based on the beacon messages of the main route nodes. Through the experiments, proposed scheme shows improvements in the data packet delivery ratio and reduces the amount of routing control message overhead compared with existing routing protocols such as Energy-Efficient Ant-Based Routing Algorithm (EEABR) and Ladder Diffusion.
    Keywords: Energy efficient routing; GPS; Energy Efficiency; WSN.
    DOI: 10.1504/IJSNET.2016.10001447
  • In-network Data Processing in Wireless Sensor Networks Using Compressed Sensing   Order a copy of this article
    by Vishal Krishna Singh, Manish Kumar 
    Abstract: One of the major energy consuming tasks in wireless sensor networks (WSNs) is the task of data transmission. The lifetime of such a network can be significantly enhanced by, minimizing the in-network transmissions and dividing the transmission load symmetrically over the network. To overcome the issues of non-uniform energy dissipation and networks lifespan, a novel hierarchical compressive sampling (HCS) scheme is proposed. Based on the well-known hybrid compressed sensing scheme, the proposed HCS aims at minimizing the overall in-network communication during the data gathering process by obtaining correlated sensor readings through a hierarchical clustering scheme. The proposed HCS is able to identify the optimal position for the application of compressed sensing (CS) in the routing structure, to achieve symmetric load distribution in a randomly deployed network. The equal distribution of transmission load is validated through a heat map generated for showing the receiving and transmission activity at each node. An energy consumption model, based on the energy required by the radio, the processor and in the CS process, is proposed and the lifetime of the network is simulated for different sink positions. Simulations prove the efficacy of the proposed HCS over various CS based data processing schemes.
    Keywords: Hybrid CS; Energy conservation; In-network transmissions; Large scale sensor network; Symmetric load distribution.
    DOI: 10.1504/IJSNET.2016.10001449
  • Lifetime Maximization of wireless sensor networks with multiple sinks using multiple paths and variable communication range   Order a copy of this article
    by Vasavi Junapudi, Siba Udgata 
    Abstract: Maximizing network life time in a wireless sensor network used for maintainingrncrucial events and parameters is an important research area. In this paper, we define the life time of the network as the number of messages it is able to transfer to the sink node. We consider multiple links and propose three different variants of the algorithm to enhance the network life time in terms of number of messages successfully transmitted to any of the sink. The first algorithm constructs tree with sink node as the root to every other node and the nodes choose the sink based on the shortest path. Sink shifting happens based on the predefined shift rate. In the second approach, we try to find alternate path to reach the same sink before finally shifting to other sink. In the third approach, we increase the communication range in stages such that, it can avoid crucial nodes and reach the sink node by spending more energy. The performance compared and shown that the network life time is enhanced with the help of second and third approach by 8.75% and 33.42% than Cluster based algorithm for sink Selection (CASS). Alternate Path with variable communication range has improved the network life time by 22.90% over Alternate Path approach.
    Keywords: Wireless Sensor Networks; Multiple Sinks; Routing; Adjustable/Variable Communication Range; Network Life Time.
    DOI: 10.1504/IJSNET.2016.10001453
  • Clustering algorithm for wireless sensor networks : the honeybee swarms nest-sites selection process based approach   Order a copy of this article
    by Ado Adamou Abba Ari, Nabila Labraoui, Blaise Omer Yenké, Abdelhak Gueroui 
    Abstract: The design of low-power, scalable and energy efficient clustering protocols in order to extend the lifetime of wireless sensor networks remain an active area of research. Cluster-based sensor networks with data aggregation on cluster heads is the most popular approach for optimizing the energy consumption of nodes, in order to maximize the overall network lifetime. Clustering is also used for optimizing QoS and scalability in sensor networks. In the case of large scale networks, the management of nodes becomes a challenge. It is therefore necessary that, these sensors act in a self-organized manner to perform tasks for the overall network. A number of novel protocols, architectures, algorithms and applications has been proposed and implemented. Swarm intelligence provides the most powerful models of social insects that provide a global intelligence through local and simple actions in a self-organized and distributed manner. In this paper, we proposed a distributed clustering approach based on the nest-sites selection process of a honeybee swarm. In the design of our proposed algorithm, we focused on the distribution of load balancing among each cluster member in order to extend network lifetime. The performance of the proposed approach was evaluated by performing extensive experiments and the results demonstrated that our algorithm delivers better performance in terms of network lifetime, amount of packets received by the base station, end-to-end delay, energy consumption and efficiency.
    Keywords: Wireless sensor networks; Clustering; Cluster Head; Swarm Intelligence; Honeybees; NEST.
    DOI: 10.1504/IJSNET.2016.10007395
  • Regression Model Based Consensus for Clock Synchronization of Wireless Sensor Network   Order a copy of this article
    by Guoyong Shi 
    Abstract: Consensus is a process of reaching an agreed state throughout a distributed network by exchanging local information. Stochastic averaging matrix operation on a subset of state vectors is an effective and scalable method for arriving at a consensus state in a finite-dimensional space. In this work we extend this principle to a novel modelbased consensus process. The model is a linear regression model that is associated to each network node. Each node updates the regression model coefficients by exchanging locally the model output only. Upon receiving a set of output messages from neighboring nodes, the receiving node makes a consensus operation (typically averaging) and uses the result to update the regression model coefficients. We show that this kind of regression-based averaging scheme is able to synchronize all model parameters throughout the network, consequently, the model outputs of all nodes would have achieved consensus as well. In the second part of this work we apply the developed method to clock synchronization problem of wireless sensor network (WSN). We treat both clock drift and offset uncertainty and model them as the regression model coefficients. By only locally exchanging clock readings between neighboring nodes, each node adjusts its drift and offset parameters. Simulation verifies that the network-wide clock readings can be synchronized gradually. The effectiveness of this synchronization method is compared to other traditional clock synchronization methods. The main advantage of the new method is its robustness and reduced variation of the clock errors, a measure that characterizes the degree of network clock consensus.
    Keywords: Clock synchronization; linear regression; model-based consensus; network coordination; wireless sensor network (WSN).
    DOI: 10.1504/IJSNET.2016.10001461
  • Lightweighted and Energy-Aware Mikey-Ticket For E-Health Applications in the Context of Internet of Things   Order a copy of this article
    by Mohammed Riyadh Abdmeziem, Djamel Tandjaoui, Imed Romdhani 
    Abstract: E-health applications have emerged as a promising approach to provide unobtrusive and customizable support to elderly and frail people based on their situation and circumstances. However, due to limited resources available in such systems and data privacy concerns, security issues constitute a major obstacle to their safe deployment. To secure e-health communications, key management protocols play a vital role in the security process. Nevertheless, current e-health systems are unable to run existing standardized key management protocols due to their limited energy power and computational capabilities. In this paper, we introduce two solutions to tailor MIKEY-Ticket protocol to constrained environments. Firstly, we propose a new header compression scheme to reduce the size of MIKEYs header from 12 Bytes to 3 Bytes in the best compression case. Secondly, we present a new exchange mode to reduce the number of exchanged messages from six to four. We have used a formal validation method to evaluate and validate the security properties of our new tailored MIKEY-Ticket protocol. In addition, we have evaluated both communication and computational costs to demonstrate the energy gain. The results show a decrease in MIKEY-Ticket overhead and a considerable energy gain without compromising its security properties.
    Keywords: E-health; Internet of Things; MIKEY-Ticket; Security; Key Management; Data Confidentiality.

  • Gateway Bandwidth Arrangement of Data Transmission in Cyber-Physical System   Order a copy of this article
    by Hao Wang, Jianzhong Li, Hong Gao 
    Abstract: Along with the development of wireless communication technology, different wireless technologies suitable for variety situations have been widely used. Wireless technologies with different characteristics have deeply promoted the development of Cyber-Physical System. Various kinds of devices such as sensors, actuators and data processors in a Cyber-Physical System have been used to complete different tasks and also be equipped with different kinds of wireless communication technologies in order to meet different needs of work. Meanwhile, all these devices have to make communication mutually to keep the whole system effective. Gateways have been used to connect these equipments with different kinds of wireless technologies. Different devoices pack information in data packets, and transmit them to each other through gateways. We propose a dynamic gateway bandwidth allocation algorithm, in order to maximize total packets delivery ratio. Simulation results have shown that this algorithm is efficient.
    Keywords: packet delivery; bandwidth allocation; hybrid wireless network; Cyber-Physical System.
    DOI: 10.1504/IJSNET.2017.10007396
  • Optimal Gateway Placement for Hybrid BANETs-Sensor Networks in Urban Areas   Order a copy of this article
    by Chunyan Liu, Hejiao Huang, Hongwei Du, Xiaohua Jia 
    Abstract: For a given urban area, sensors are well deployed in each subareas divided by streets. We apply the existing Bus-based Adhoc Networks (BANETs) to collect and transmit information from subareas to the data center, which can significantly reduce the number of sensors and the information transmissions. WSNs and BANETs are heterogeneous, and minimal number of gateways are required to connect them because of the higher cost of gateways. In this paper, we propose two gateway placement problems: minimum gateways placement and minimal gateways placement with minimum average delay. We present a (1+ln r)-approximation algorithm and r-approximation algorithm to solve the two problems, where r is the maximum number of subareas covered by a gateway candidate. In the geometric topology of the grid urban area, r<= 4. Extensive comparison simulation show the performance of minimum gateways and minimal gateways with minimum average delay achieves significantly.
    Keywords: wireless sensor networks; Bus-based adhoc networks; gateway placement; approximation algorithm.
    DOI: 10.1504/IJSNET.2017.10007401
  • System-Level Analysis of IEEE 802.11ah Technology for Unsaturated MTC Traffic   Order a copy of this article
    by Aleksandr Ometov, Nader Daneshfar, Ali Hazmi, Sergey Andreev, Luis Felipe Del Carpio, Parth Amin, Johan Torsner, Yevgeni Koucheryavy, Mikko Valkama 
    Abstract: Enabling the Internet of Things, machine-type communications (MTC) is a next big thing in wireless innovation. In this work, we concentrate on the attractive benefits offered by the emerging IEEE 802.11ah technology to support a large number of MTC devices with extended communication ranges. We begin with a comprehensive overview of the novel features introduced by the latest IEEE 802.11ah specifications following by development of a powerful mathematical framework capturing the essential properties of a massive MTC deployment with unsaturated traffic patterns. Further, we compare our analytical findings for a characteristic MTC scenario against respective system-level simulations across a number of important performance indicators. Our analytical results give adequate performance predictions even when simulations are challenged by the excessive computational complexity. In addition, we study the novel IEEE 802.11ah mechanisms offering improved support for massive device populations and conclude on their expected performance.
    Keywords: IEEE 802.11ah; analytical modelling; simulations; MTC/M2M; unsaturated traffic; throughput; delay; power consumption.
    DOI: 10.1504/IJSNET.2017.10007402
  • An intelligent closed-loop learning automaton for real-time congestion control in wireless body area networks   Order a copy of this article
    by Samia Allaoua Chelloug 
    Abstract: Recently, a considerable literature has grown up around the theme of Wireless Sensor Networks (WSNs) that are investigated in many applications. So far, Wireless Body Area Networks (WBANs) have emerged as a flexible solution for remote monitoring of mobile patients, nurses and elderly people. Nevertheless, WBANs are challenged by the real-time constraints of medical data. By another hand, WBANs have limited communication and computation capabilities. So, the collected physiological data should be aggregated before being sent to the base station. Moreover, the aggregation process may lead to the congestion problem. In this paper, we propose a closed-loop learning automaton that is based on conditional probabilities to assign each packet to the appropriate queue given the criticality of the sensed data. Our Omnet++ simulation results have been analysed using the Z-test. They confirm the performance of our scheme in terms of the drop ratio and the throughput.
    Keywords: WSNs; WBANs; congestion; learning; criticality; real-time; closed-loop; open-loop; drop ratio; throughput; Bayes rule; Omnet++; Z-test.
    DOI: 10.1504/IJSNET.2017.10007404
  • On Reliable Data Delivery in Stochastic Energy Harvesting Wireless Sensor Networks   Order a copy of this article
    by Zheng Liu, Xinyu Yang, Wei Yu 
    Abstract: In wireless sensor networks (WSNs), sensor nodes with energy harvesting components have motivation to expend additional energy in conditions of excess, since the surplus energy would be wasted due to energy buffer overflow. In this paper, we focus on using such surplus energy to adjust the redundancy level of erasure codes, so that the data delivery reliability can be improved while the network lifetime is still well conserved. For a single flow, we formulate the problem as the maximization of end-to-end packet delivery probability under energy constraints. Considering the energy profile as a stochastic process, we propose a Lyapunov optimization based algorithm called the Erasure Coding Scheduling Algorithm (ECSA) to solve the problem. ECSA jointly manages the energy, adjusts the redundancy level of erasure codes and makes forwarding and receiving decisions for packet transmissions. ECSA does not require any knowledge of the harvestable energy and achieves an end-to-end packet delivery probability within $e^{-varepsilon-C}$ of optimal, while ensuring the required energy buffer size and the network congestion, which are bounded by size $O(1/varepsilon)$ for any $varepsilon>0$. Through a combination of both theoretical analysis and simulation, we show the effectiveness of ESCA in yielding a near-optimal data delivery reliability. We also show that ESCA can be easily adapted to multi-flow cases and implemented in a distributed manner.
    Keywords: Erasure Codes; Stochastic Energy Harvesting; and Lyapunov Optimization.
    DOI: 10.1504/IJSNET.2017.10007405
  • Data Delivery in Wireless Sensor Networks with Uncontrollable Mobile Nodes   Order a copy of this article
    by Hosam Rowaihy, Ahmed Binsahaq 
    Abstract: Wireless sensor networks (WSNs) consist of low-powered devices that have computation, wireless communication and environment-sensing capabilities. These low-cost sensors are usually deployed in a dense and stationary manner for the periodic sensing of environmental phenomena. WSNs open the door for many monitoring applications in the military, in healthcare, and in environmental and urban studies. Mobile Wireless Sensor Networks (MWSNs) are a subclass of WSNs in which some or all the sensors are mobile. Many environmental applications are designed and deployed on top of MWSNs in which the sensors hosts are uncontrolled by end users (e.g., the OpenSense project for air pollution monitoring in the city of Zurich). MWSNs pose many challenges for newly designed applications. In this paper, we evaluate MWSNs with a location-based application. We test various data delivery schemes used by sensors in MWSNs, including GPRS, Wi-Fi, and Hybrid (both GPRS and Wi-Fi). We perform extensive simulation-based experiments using the ns2 simulator.
    Keywords: WSNs; wireless sensor network; MWSNs; mobile wireless sensor network; mobility; mobile sensors; performance evaluation.
    DOI: 10.1504/IJSNET.2017.10007407
  • Quality of Service Control in Proactive Wireless Sensor Networks via Lifetime Planning   Order a copy of this article
    by Peilin Zhang, Mohamed Abdelaal, Oliver Theel 
    Abstract: Successful exploitation of Wireless Sensor Networks (WSNs) is intuitively dependent on the enabling technologies as well as on the provision of application-relevant Quality of Service (QoS) metrics. Current research efforts mostly focus on maximizing the network lifetime without considering the predefined task time. In this article, we firstly provide a survey and a classification of the current state of QoS control methods in WSNs. Subsequently, we propose a novel QoS control method, referred to as lifetime planning. Based on design-time knowledge, lifetime planning provides users/applications with best-effort QoS, while meeting the time span required to complete the assigned task. To this end, an "upper" and a "lower" QoS boundary have to be defined for every QoS metric at the design-time. During run-time, a self-adaptation framework confines the QoS metrics between these boundaries. Lifetime planning outperforms other fixed heuristics and blind adaptation methods. As another proof of concept, we consider an office monitoring scenario with a cluster-tree WSN topology for performance evaluation. The scenario has been designed in the Contiki-OS network simulator, Cooja, using Tmote sky motes. Moreover, a novel QoS model has been engineered to determine the QoS boundaries. Simulation results show that lifetime planning tremendously improves the provided QoS while meeting the task lifetime.
    Keywords: Wireless Sensor Networks; QoS Control; Survey; Energy Management; Lifetime Planning; Self-adaptation.

  • Clustering-Based Energy-Efficient Routing Approach for Underwater Wireless Sensor Networks   Order a copy of this article
    by Gurkan Tuna 
    Abstract: As a result of the time-varying and harsh environment conditions, in underwater wireless sensor network (UWSN) scenarios, along with the excessive error rate of acoustic channels and long propagation delays, one of the most critical issues which must be addressed is to minimize energy consumption of sensor nodes. Moreover, it is hard to replace the batteries of the underwater sensor nodes frequently, therefore extending the lifetime of the nodes is one of the most important design objectives. In UWSNs, although energy dissipation in transmission mainly depends on employed routing algorithms and media access control (MAC) schemes, given the nature and challenges of the acoustic communication in water, all the layers of the protocol stack play an important role on achieving a high energy efficiency. Therefore, novel approaches that handle energy inefficiencies and extend the lifetime of UWSNs are required. In this paper, we propose an energy-efficient routing approach called Clustering-Based Energy-Efficient Routing (CBEER) to prolong the lifetime of UWSNs and evaluate its performance through extensive simulations. Based on a novel clustering-based scheme, the proposed approach can find shortest routing paths to carry data packets and is able to realize uniform network energy consumption profile in the entire underwater sensor network. The simulation based evaluation studies reveal that CBEER performs well in terms of packet delivery ratio and overall network energy consumption.
    Keywords: Clustering; Energy Efficiency; Routing; Underwater Wireless Sensor Network.
    DOI: 10.1504/IJSNET.2017.10007409
  • Cooperative Stackelberg Game Based Optimal Allocation And Pricing Mechanism In Crowdsensing   Order a copy of this article
    by Chunchi Liu, Rong Du, Shengling Wang, Rongfang Bie 
    Abstract: Crowdsensing has been earning increasing credits for effectively integrating the mass sensors to achieve significant tasks that one single sensor cannot imagine. However in many existing works in this field, some key information of the participants is incomplete to each other, hence causing the non-optimality result. Noticing that a potential cooperation between the players, we propose the cooperative Stackelberg game based optimal task allocation and pricing mechanism in a crowdsensing scenario. Aiming at different optimizing criteria, we propose two optimal Stackelberg games that are either with no budget constraint (No-Budget OpSt Game) or with budget constraint (Budget- Feasible OpSt Game). Analysis of their corresponding Stackelberg Equilibrium is then presented. Lastly, we perform extensive simulations to test the impact of the parameters on our model. Results of our two proposed games are progressively compared to show their optimizations in their respective criteria.
    Keywords: Crowdsensing; Stackelberg game; Optimal Mechanism; Budget Feasible; KKT conditions.
    DOI: 10.1504/IJSNET.2017.10007410
  • Maximizing Influence in Sensed Heterogenous Social Network with Privacy Preservation   Order a copy of this article
    by Meng Han, Qilong Han, Lijie Li, Ji Li, Yingshu Li 
    Abstract: Maximizing influence in a specific scenario to improve the performance of marketing has a significant impact on targeted advertisements and viral product promotion, which has became one of the most fundamental problems in social data analysis. Many attentions have been paid to extensively analyze the influence in social data. However, most of the existing works, unfortunately, neglect the fact that the sensed location data in the cyber physical world could also play an important role in the influence prorogation process. Furthermore, even though a few works consider a little sensed information to enhance the influence maximization, the privacy protection issue of the sensed data (location, social relationship) was directly exposed to the public. This paper considers the problem of maximizing influence in both sensed location Data and Online Social Data with privacy preserving. We firstly merge both the sensed location data from cyber-physical network and relationship data from online social network into a unified framework with one novel model, then an efficient algorithm to solve the influence maximization problem are provided within our resolution. Besides, our model could not only support our influence maximization problem, but also support other applications related to both sensed location data and online social data. Furthermore, our privacy-preserving mechanism could protect the sensitive location and link information during the whole process of data analysis. Real life datasets are empirically tested with our framework and demonstrate the power of sensed and online data combination to influence maximization.rnThe experiment result also suggests that our framework is outperforming most of the existing alternative resolutions and succeeds in preserving privacy while other resolutions not.
    Keywords: Sensed Data; Location; Social Network; Data Privacy; Influence Maximization.
    DOI: 10.1504/IJSNET.2017.10007412
  • Rotation Based Coverage Control Algorithm and Protocol for Heterogeneous Sensor Networks   Order a copy of this article
    by Quanlong Li, Qing Yang, Lu Su 
    Abstract: This paper studies the problem of coverage control, one fundamental issue in wireless sensor networks (WSN). In many applications of WSN, the target area is required to be covered for a certain degree. To satisfy coverage requirements, redundant sensors are usually deployed, which may cause unnecessary energy consumption on sensor nodes. To address this challenge, some coverage control methods have been proposed to reduce the number of active sensors and prolong the lifetime of sensor networks. However, none of them can be applied to heterogeneous sensor networks that are composed of different types of sensors with different sensing radii. In the previous work[1], this problem was solved by a novel coverage control mechanism for heterogeneous sensor networks. This mechanism, unfortunately, still suffers from a major limitation. That is, it may exhaust the energy of the active sensors, leading to unbalanced energy consumption among the sensor nodes. To tackle this problem, in this paper, we propose a novel distributed rotation based coverage control strategy for heterogeneous sensor networks. This strategy only needs to analyze a few special points coverage to determine each sensor node's working schedule, and thus can significantly reduce the complexity of coverage computation. Theoretical analysis and simulation results show that the proposed coverage control algorithm and protocol can outperform prior work in terms of not only the energy saving but also the energy balancing.
    Keywords: Rotation-based Coverage; Coverage Control; Wireless Sensor Networks.
    DOI: 10.1504/IJSNET.2017.10007413
  • A Novel Task Recommendation Model for Mobile Crowdsourcing Systems   Order a copy of this article
    by Yingjie Wang, Xiangrong Tong, Kai Wang, Baode Fan, Zaobo He, Guisheng Yin 
    Abstract: With the developments of sensors in mobile devices, mobile crowdsourcing systems are attracting more and more attention. How to recommend user-preferred and trustful tasks for users is an important issue to improve efficiency of mobile crowdsourcing systems. This paper proposes a novel task recommendation model for mobile crowdsourcing systems. Considering both user similarity and task similarity, the recommendation probabilities of tasks are derived.\r\nBased on dwell-time, the latent recommendation probability of tasks can be predicted. In addition, trust of tasks is obtained based on their reputations and participation frequencies. Finally, we perform comprehensive experiments towards the Amazon metadata and YOOCHOOSE data sets to verify the effectiveness of the proposed recommendation model.
    Keywords: Mobile crowdsourcing systems; Recommendation model; Similarity; Dwell-time; Trust.
    DOI: 10.1504/IJSNET.2017.10007414
  • Minimum Cost Flow Based Approach for Connectivity Restoration in WSN   Order a copy of this article
    by Eman Shaaban 
    Abstract: A WSN consists of resourced-constrained sensor nodes that cooperate to accomplish specific tasks. In many applications, WSNs operate unattended in harsh environments, which make sensor nodes susceptible to failure due to physical damage or depletion of onboard energy supply. Some of the nodes are critical to the network connectivity and their failure may partition the network into multiple disjoint segments. WSN can autonomously recover from this failure through relocation of some nodes. However such a recovery process remains challenging since tolerating the failed nodes individually is not a globally optimal solution and may cause resource conflict. This paper presents a Recovery approach that forms a topology with Increased Robustness against recurrent failure (RIR). RIR tolerates the failure of multiple connectivity-critical nodes through repositioning of non-critical healthy nodes. RIR can handle multiple simultaneous failures of either collocated or scattered nodes. The approach favors substituting a failed node with one with the highest residual energy in order to sustain the network connectivity for the longest time possible. RIR models the recovery as a Minimum Cost Flow (MCF) problem to determine the best set of node relocations for repairing the network topology while minimizing the motion overhead of the recovery process. The performance of RIR is evaluated through extensive simulation experiments. The simulation results have confirmed the effectiveness of the proposed scheme.
    Keywords: wireless sensor networks; connectivity restoration; node relocation; minimum cost flow; WSN recovery.
    DOI: 10.1504/IJSNET.2017.10007415
  • Accuracy-aware Data Collection in Wireless Sensor Networks   Order a copy of this article
    by Ran Bi, Xu Zheng, Guozhen Tan 
    Abstract: Data collection is a fundamental task in Wireless Sensor Networks. In many practical applications, approximate results with error bound guarantee can satisfy user requirements. To approximate sensed data, the filter based approach is to maintain the filters of each node at both sensor node and base station. The filter of each node is represented by an interval. For a given filter, the sensor node sends the update to the base station if the sensed data is beyond the range of the filter. In this paper, we investigate the accuracy-aware approach for approximate data collection. The filter assignment for optimizing the average of valid filter time is formalized as an integer optimization problem and the hardness of this problem is proven to be NP-Complete. A greedy heuristic based algorithm with low computation overhead is proposed. Moreover, to balance the valid filter time, the filter assignment for optimizing the minimum valid time is formalized as a general max-min problem. We analyze the hardness of the problem and propose an approximation algorithm. The experimental results show that our algorithms achieve better results in terms of communication cost and expected time of valid filters.\r\n
    Keywords: Data Collection; Sensed Data Model; Approximate Algorithms; Wireless Sensor Networks.
    DOI: 10.1504/IJSNET.2017.10007416
  • GRACO: a geographic GReedy routing with an ACO based void handling technique   Order a copy of this article
    by Mouna Rekik, Nathalie Mitton, Zied Chtourou 
    Abstract: Geographic routing has gained much attention as a basic routing primitive in wireless sensor networks due to its memory-less, scalability, efficiency and low overhead features. Greedy forwarding is the simplest geographic routing scheme, it uses the distance as a forwarding criterion. Nevertheless, it may suffer from communication holes, where no next hop candidate is closer to the destination than the node currently holding the packet. For this purpose, a void handling technique is needed to recover from the void problem and successfully deliver data packets if a path does exist between source and destination nodes. Many approaches have been reported to solve this issue at the expense of extra processing and or overhead. This paper proposes GRACO, an efficient geographic routing protocol with a novel void recovery strategy based on ant colony optimization (ACO). GRACO is able to adaptively adjust the forwarding mechanism to avoid the blocking situation and effectively deliver data packets. Compared to GFG, one of the best performing geographic routing protocols, simulation results demonstrate that GRACO can successfully find shorter routing paths with higher delivery rate, less control packet overhead and shorter end-to-end delay.
    Keywords: wireless sensor networks ; geographic routing ; guaranteed delivery ; swarm intelligence ; ant colony optimization.
    DOI: 10.1504/IJSNET.2017.10007419
  • A Radio Link Reliability Prediction Model for Wireless Sensor Networks   Order a copy of this article
    by Wei SUN, Qiyue Li, Jianping Wang, Liangfeng Chen, Daoming Mu 
    Abstract: The Wireless Sensor Network (WSN) has great prospects in monitoring and control of industrial plants and devices. One of the main challenges of developing WSNs for industrial applications is to satisfy their requirements for reliability with strict bounds. Accurate prediction of a radio links reliability is helpful for upper layer protocols to optimize network level Quality of Service performance. In this paper, to predict the bounds of the confidence interval of the Packet Reception Ratio (PRR), a Radio Link Reliability Prediction (RLRP) model is proposed for describing the relation between the reliability metrics bounds and factors that affect it. Based on the RLRP model, the adaptive extended Kalman filter algorithm is adopted to predict the reliability metric. Real world experiments were performed to demonstrate the proposed model. The results indicate that our RLRP model is accurate in predicting the bounds of link reliability, can better reflect the random characteristic of the radio link, and is more sensitive to dynamic changes of the radio link.
    Keywords: Link Reliability Model; Reliability Prediction; Wireless Sensor Network; Kalman Filter.
    DOI: 10.1504/IJSNET.2017.10007422
  • Cross-layer control of wireless sensor network for smart distribution grid   Order a copy of this article
    by Ruju Fang, Jianping Wang, Wei Sun 
    Abstract: This article presents an integrated modeling method providing cross layer control for Wireless Sensor Networks (WSNs) communication which is suitable for Smart Distribution Grid (SDG). There are multiple protocol layers in WSNs communication. In order to meet the Quality of Service (QoS) of application for WSNs, as well as more resource-efficient for the resource-constrained nodes, a cross-layer control algorithm based on theory of Fuzzy Cognitive Map (FCM) is proposed. The cross layer control model of the whole communication system is established by utilizing different influence coefficients among fuzzy cognitive map concepts which represent the subordinate relationships of different protocol layers, such as application layer, network layer, MAC layer and physical layer. Influence coefficients among fuzzy cognitive map concepts can be obtained self-learning and self-training way, which can timely adjust the physical layer,MAC layer,transport layer parameters and routing strategy based on the network environment and control needs.rnFinally, communication performance of cross layer control algorithm is evaluated by received data of WSNs network,the average delay and effective throughput, and so on. Results show that cross layer control scheme based on fuzzy cognitive map proposed in paper can meet the real-time and reliability requirements.rn
    Keywords: Smart distribution grid; Wireless sensor network; Fuzzy cognitive map; Back-off strategy; Cross layer control.

  • Aggregation Aware Early Event Notification Technique for Delay Sensitive Applications in Wireless Sensor Networks   Order a copy of this article
    by Sukhwinder Singh Sran, Jagpreet Singh, Lakhwinder Kaur 
    Abstract: In this paper, an aggregation aware early event notification technique (AAEENT) is proposed for WSNs characterized by unpredictable events. The novelties of the proposed technique are two folds. First, reliable routing policy is proposed to deliver events data over high throughput paths to final destination as early as possible. This reliable routing policy minimizes the number of retransmissions, which in turn reduces network congestion. Second, temporal data aggregation has been used to minimize redundant data at each intermediate node. The proposed technique has been implemented by incorporating proposed policy in Collect protocol of Contiki operating system and is evaluated over Cooja network simulator. For performance analysis, the results are compared with the Constant Delay based aggregation, Random Waiting based aggregation policy and the existing Collect Protocol. From the results, it has been observed that due to reduced network bottlenecks in the proposed technique, the event notification time declined upto 35% and overall power consumption is reduced upto 37% in contrast to existing solutions.
    Keywords: Data Aggregation; Energy Consumption; Energy Efficient Routing; Event Notification Time; Wireless Sensor Networks.
    DOI: 10.1504/IJSNET.2017.10007423
  • Flooding in 3-Dimensional Mobile Ad Hoc Networks Using 1-Hop Information   Order a copy of this article
    by Xin Bai, Xiaohui Wei, Sen Bai 
    Abstract: Flooding is a fundamental problem in mobile ad hoc networks (MANETs). Traditional pure flooding suffers from excessive redundancy of transmissions, which causes high overhead and severe interference of the network. Therefore, many flooding algorithms have been proposed to reduce the redundancy of messages. However, former works mostly focus on 2-dimensional MANETs, and their approaches are hard to be extended to 3-dimensional wireless networks. In this paper, we consider the flooding problem for 3-dimensional MANETs. We propose an efficient flooding algorithm using only 1-hop neighbours information to optimize running time of the algorithm. Under the premise of ensuring full delivery, the proposed algorithm selects a minimum set of neighbours for each node to forward messages for reducing redundant transmissions. Simulations have been conducted and the results have shown that the proposed algorithm significantly decreases required transmissions for a flooding.
    Keywords: flooding; mobile ad hoc network; 3-dimensional wireless network.
    DOI: 10.1504/IJSNET.2017.10007424
  • Design and Performance Analysis of Two-Stage Contention MAC Protocol for Full-Duplex Wireless Networks   Order a copy of this article
    by Yanguo Zhou, Hailin Zhang, Ruirui Chen, Tao Zhou 
    Abstract: Full-duplex (FD) wireless communications, which allow the co-time co-frequency transmission and reception, have received significant attentions in recent years. Newly emerged advanced cancellation schemes can efficiently mitigate the self-interference caused by the FD wireless communication, thus achieving high spectrum efficiency in the physical-layer as compared with the traditional half-duplex (HD) communications. However, not only the high spectrum efficiency is highly demanded in the physical-layer, but also the high throughput of the data-link layer is urgently needed, resorting to the efficient full-duplex medium access control (FD-MAC) protocol. In this paper, we propose the two-stage-contention based medium access control protocol for full-duplex wireless networks (TF-MAC) to optimize the throughput of FD wireless networks. First, we design a request to send (RTS)/full-duplex clear to send (FCTS)/clear to send (CTS) based handshaking mechanism. Then, the FD back-off algorithm is proposed to reduce the collisions for FD transmissions among all nodes. Finally, based on the two-dimensional Markov chain, we derive the closed-form expression for the throughput of FD wireless networks. The simulation results demonstrate the performance of our proposed TF-MAC protocol.
    Keywords: full-duplex communication; medium access control protocol; request to send/full-duplex clear to send/clear to send handshaking mechanism; full-duplex back-off algorithm; two-stage-contention.

  • Delay Minimizing Depth Based Routing for Multi-Sink Underwater Wireless Sensor Networks   Order a copy of this article
    by Chaitanya Kumar Karn, C.P. Gupta 
    Abstract: Underwater acoustic network is the enabling technology for number of applications viz. ocean exploration, pollution monitoring, etc. Each application requires appropriate network resources. Routing in such networks is challenging due to longer delays and mobility caused due to ocean currents and tides. Existing routing algorithms focus only on delivery of packets with very little consideration to minimizing delay in packet delivery. In this paper, we propose a new beacon-based routing algorithm for underwater sensor networks using multiple sink architecture. DMDBR (Delay Minimizing Depth Based Routing) attempts to minimize delay and uses depth, hop count and possible energy information for making routing decisions. Novelty of our scheme is in a node accepting packets for forwarding if it has sufficient residual energy to forward all the packets in the packet queue. A node declines acting as a forwarder once the estimated residual energy is not sufficient to forward the new packets. Simulation results show that DMBDR improves packet delivery ratio and minimize end-to-end delay in comparison to Depth Based Routing.
    Keywords: Underwater Wireless Sensor Networks (UWSN); Forwarding Factor (FF); Delay Minimizing Depth Based Routing (DMDBR); Beaconing Interval.

  • A Representative Node Selection based Data Gathering Method for Compressive Sensing in WSNs   Order a copy of this article
    by Chengyang Xie, Jiancong Zhao, Yugang Niu 
    Abstract: In traditional compressive data gathering (CDG) , many rounds of data gathering are required to make sure the accuracy of reconstruction signal such that most of nodes are required to participate in data gathering. By using the spatial and temporal correlation character of sensor readings, we propose a compressive data gathering method based on representative node selection (RNS-CDG) to collect measurement vector via just one routing tree. By means of principal component analysis (PCA) and frame potential (FP), the proposed method can select fewer representative nodes from all nodes, by which a data gathering tree will be constructed. And then, via this routing tree, a measurement vector composed of M projections will be received by Sink for recovering signal. It is shown via simulation results that the proposed method can ensure the accuracy of data reconstruction and reduce the transmissions of network.
    Keywords: Compressive data gathering; spatiotemporal correlation; representative node selection; wireless sensor networks.

  • A Study of Mobile CDSS for Cardiovascular Disease Diagnosis   Order a copy of this article
    by Young-Keun Lee, Sang-seok Yun, Jae-young Choi, Malrey Lee 
    Abstract: Although cardiovascular diseases are the number one cause of death globally, they are often diagnosed in hospitals during the late stages of life. This paper aims to make a cardiovascular disease diagnose system in the mobile environment using the Artificial Neural Network. Survey data has been collected from public institutions based on characteristics including, gender type, age, height, weight, body mass index, high blood glucose, heart rates, end-systolic and end-diastolic pressure, history of cardiac infarction and angina pectoris. The collected data is manipulated through training functions. The training functions are compared using Bayesian Regulation back propagation and Levenberg-Marquardt back propagation. Subsequently, the computed results are analyzed which show significant performance. Finally, the results are analyzed by using performance functions: Mean Squared Error and Sum Squared Error. Consequently, this study validates the accuracy of cardiovascular disease diagnosis by comparing with error rates, trained results, and the actual data.
    Keywords: Mobile Clinical Decision Supporting System; Cardiovascular Diagnosis; Artificial Neural Network; sensor.

  • A dynamic advertisement interval strategy in bluetooth low energy networks   Order a copy of this article
    by Jihun Seo, Changsu Jung, Bhagya Silva, Kijun Han 
    Abstract: Nowadays, many investigators have examined the effects of Bluetooth Low Energy (BLE) for a wide range of applications due to its low-cost and low-power characteristics. Hence, Performance improvement during the discovery process has become one of major concerns. In BLE networks, advertisement interval of advertiser directly influences the performance factors, such as discovery latency and energy consumption, since the advertiser discovers scanners by transmitting advertising Packet Data Units (PDUs). Frequent transmissions of advertising PDUs may result in collisions and serious energy consumption issues. On the contrary, larger advertisement interval may lead to delayed device discovery. In this paper we propose an improved algorithm to enable advertisers to adjust its advertisement interval with respect to the network conditions based on a Carrier Sensing (CS) scheme. The proposed algorithm acquires the network conditions by listening advertising channels before transmission of advertising PDUs, while allowing the advertisers to adjust their parameters accordingly. Simulation results show that the proposed algorithm has outstanding performance compared with basic CS scheme and BLE standard in crowded BLE networks.
    Keywords: Bluetooth Low Energy (BLE); Device Discovery; Internet of Things (IoT); Dynamic Advertisement Interval.

  • Joint Spectrum Access and Transmission Power Management for Energy Harvesting Cognitive Radio Sensor Networks   Order a copy of this article
    by Fan Zhang, Tao Jing, Yan Huo, Kaiwei Jiang 
    Abstract: In this paper, we investigate the joint optimization of spectrum access and the transmission power for an energy harvesting cognitive sensor node, which operates in time-slotted fashion with causal knowledge of channel conditions along with the energy harvesting states. Allowing for the stochastic behavior of the primary channel status as well as the sensing imperfection, we formulate this joint optimization problem as an infinite-horizon discrete-time Markov decision process, in which the cognitive sensor node aims at maximizing the long-term expected throughput. Through using the value iteration approach, an optimal policy which specifies the spectrum access decision as well as the power level to be used upon the transmission is proposed. A theoretical analysis is conducted for the optimal policy, it is indicated that the optimal long-term expected throughput is non-decreasing with the battery available energy. Moreover, in order to reduce the computational complexity, we introduce a low-complexity policy and prove that the optimal low-complexity policy has a threshold structure with respect to the battery available energy. Based on this threshold structure, an efficient algorithm for deriving the optimal low-complexity policy is introduced. Finally, numerical results are presented to confirm the superiority of our proposed policies to other existing policies, and it demonstrates that the optimal low-complexity policy achieves a comparable performance with the optimal policy.
    Keywords: Energy Harvesting; Cognitive Radio; Markov Decision Process; Sensor Networks.

  • Object Localization through Clustering Unreliable Ultrasonic Range Sensors   Order a copy of this article
    by Lei Pan, Xi Zheng, Philip Kolar, Shaun Bangay 
    Abstract: The increasing popularity and availability of inexpensive ultrasonic sensors facilitates opportunities for tracking moving objects by using a cluster of these sensors. In this paper, we use a cluster of ultrasonic sensors connected to Raspberry Pis. We conduct field tests and discover that their accuracy and reliability of individual sensors depends on the relative position of the tracked object. Hence, we employ data fusion and synchronization techniques for trilateration to improve accuracy using a cluster of sensor nodes. We successfully conduct multiple runs tracking a moving object and report these field test results in this paper. Our average error is in the order of tens of centimeters, and some of our best results match published results for larger clusters.
    Keywords: Ultrasonic Sensor; Sensor Network; Object Tracking; Trilateration; Data Fusion.

  • A Distributed Anomaly Detection Model for Wireless Sensor Networks Based on the One-Class Principal Component Classifier   Order a copy of this article
    by Murad Rassam, Mohd Aizaini Maarof, Anazida Zainal 
    Abstract: The use of Wireless Sensor Networks (WSN) is increasing in various applications with the emergence of the Internet of Things concept which facilitates human life by equipping a sensor for each object/thing to build a network of things. Nonetheless, the sensed data quality and reliability are sometimes affected by factors such as sensors faults, intrusions and unusual events among others. Consequently, the real time and effective detection mechanisms of such anomalous data are necessary to guarantee making reliable decisions. In this paper, we propose a One-Class Principal Component Classifier (OCPCC) based distributed anomaly detection model for WSN. The proposed model utilizes the spatial correlations among sensed data in a closed neighbourhood by distributing the detection process over the nodes in a cluster-based WSN. The feasibility of the proposed model was validated using datasets collected from real world sensor network deployments and compared with local detection and some existing detection approaches from literature. The results show that the proposed distributed model helps to improve the detection rate of anomalous data compared to local model. A comparison with existing distributed models reveals the advantages of the proposed model especially for efficiency metrics while achieving better or comparable detection effectiveness.
    Keywords: Wireless Sensor Networks; Distributed Anomaly Detection; Sensor Data Analysis; Principal Component Analysis.

  • Detecting occupancy and social interaction via energy and environmental monitoring   Order a copy of this article
    by Antonino Crivello, Fabio Mavilia, Paolo Barsocchi, Erina Ferro, Filippo Palumbo 
    Abstract: The demand for human oriented services in indoor environment has received steady interest and it is represent a big challenge for increasing the human well-being. In this work, we present a system able to perform room occupancy detection and social interactions identification, using data coming from both energy consumption information and environmental data. We also study the application of supervised and unsupervised learning techniques to the reference scenario, in order to: i) infer context information related to socialization aspects, by recognizing in real-time social interactions; ii) identify when a room is really occupied by workers or not, for emergencies management. The system has been tested in a real workplace scenario, inside three rooms of the CNR research area in Pisa occupied by different numbers of workers, representing the main core technology for future Active and Assisted Living services.
    Keywords: Occupancy Detection; Social Interactions; Wireless Sensor Network.

  • Passive and Greedy Beaconless Geographic Routing for Real-time Data Dissemination in Wireless Networks   Order a copy of this article
    by Yongbin Yim, Jeongcheol Lee, Euisin Lee, Sang-Ha Kim 
    Abstract: Real-time geographic routing is one of the most popular examples relying on a greedy algorithm to deliver real-time data in wireless networks. In this routing, each sender node decides a next-hop node as a local optimum among one-hop neighbors for achieving the global real-time requirement. However, this sender-side decision paradigm suffers from periodic and network-wide beacon exchange overhead to figure out neighbor nodes. To overcome the limitation, this paper newly suggests a passive and greedy routing algorithm, called PGBR for low-cost real-time data dissemination in beaconless wireless networks. To do this, PGBR forwards real-time data by a receiver-side competition without gathering information of neighbor nodes. To achieve the passive and greedy real-time routing, PGBR focuses on two major challenging issues: a delay estimation procedure and a contention function design. The delay estimation procedure estimates both competition delay and packet transmission delay used as inputs for the contention function design. PGBR also redesigns receiver-side contention function with deliberating the estimated delay and discuss combinations with important performance metrics: residual energy and forward progress. The experimental results show that PGBR could improve the energy-efficiency as well as keeps high delivery deadline success ratio.
    Keywords: Beaconless; Real-time; Delay estimation; Contention function; Routing protocol.

  • A qualitative study of medium access control protocols supporting mobility in wireless sensor networks   Order a copy of this article
    by Zakaria Hamidi-Alaoui, Abdelbaki El Belrhiti El Alaoui 
    Abstract: In many wireless sensor network (WSN) applications, mobility support has been steadily becoming an important factor in achieving specific tasks. Nevertheless, mobile WSNs are facing several challenges and constraints regarding the wireless medium access which have been already addressed by existing Medium Access Control (MAC) protocols. In fact, these protocols were designed to handle node mobility by considering energy-efficiency and ensure medium access for all network nodes. In our work, we propose a decision-support tool enabling to choose adequate MAC protocol(s) that meet the requirements of a specific target mobile WSN application. This tool will be based on a deep analytical and comparative study of MAC protocols in terms of energy consumption and latency in dynamic contexts. Finally, we apply this approach on an application of wild animals monitoring as an example in order to retain, among the studied MAC protocols, the well-suited ones.
    Keywords: wireless sensor network; WSN; mobile WSN; medium access control; MAC; MAC protocol; mobility; mobile node; handover; decision support; latency; energy efficiency.

  • Creating a secure index for distributed data on the sensor network   Order a copy of this article
    by Vandana Bhasin, P.C. Saxena, C.P. Katti 
    Abstract: Wireless sensor networks that are deployed in public, untrusted or hostile environments, are prone to various security vulnerabilities. In this paper, a method has been developed to reduce the security risk of a node from tampering. The sensed data is distributed using the roots of the polynomial equation, thereby reducing the security risk (A & Kak S, 2009). The number of partitions are fixed as specified by the roots of polynomial equation. We propose a security mechanism on a clustered heterogeneous network: Secure Index on distributed data. The index is created for every partition before encryption. The index allows for efficient retrieval of data as it is located on cluster head. In this paper, we provide end-to-end confidentiality is not decrypted at the cluster head. The encrypted data can be decrypted only at the base station which has the key for decryption. It offers single value granularity as index is created for each unique data item in the partition. It provides data confidentiality, authentication and authorization. We have analysed the performance of the algorithm in terms of energy consumption. The energy consumption with the addition of security features has increased. We have found that even though the energy consumption has increased, the network can fulfil the purpose of data collection and can be deployed on large scale networks.
    Keywords: sensor networks; data partitioning; indexing; implicit security.

  • Distance Vector hop localization algorithm based on the limitation by the probability to hops   Order a copy of this article
    by Xin Shi, Yanping Li, Sen Zhang 
    Abstract: Distance Vector-Hop localization algorithm, using flooding routing broadcast anchor node information, is confronted with the problem of communication consumption. Using the product of jump distance correction value and the minimum number of hops to represent the distance between the nodes, can lead to cumulative error. Using maximum likelihood estimation method to determine the unknown nodes, it suffers from the excessive computational consumption. This paper presents a new algorithm. Based on the probability property of random distribution of wireless sensor network, our algorithm limits hops between nodes to reduce the network communication consumption and minimize the cumulative error in distance calculation. Moreover, trilateral positioning method or the extended MIN-MAX algorithm, which is employed to calculate the unknown node coordinates, can decrease the computational consumption. Performance analysis and simulation results show that, the proposed algorithm can achieve multi-objective optimization with higher precision and lower cost.
    Keywords: DV-HOP; probability distribution; limited number of hops; angle threshold; extended MIN-MAX.

  • Energy-Efficient Transmission Approach Using Regionalization Compressed Sensing   Order a copy of this article
    by Hao Yang, Xiwei Wang 
    Abstract: In the process of transmission in wireless sensor network, a vital problem is that a centre region closed to the sink will form in which sensors have to cost vast energy. To energy-efficient communication, Compressive Sensing(CS) has been employed gradually. However, the performance of plain CS deeply depends on the specific data gathering strategy in practice. In this paper, we propose an energy-efficient data gathering scheme based on regionalization CS. Firstly, the network is divided into several blocks randomly with no need for relationships or features among sensors. Furthermore, centre sensors for each region are elected with randomization. Subsequently, CS is implemented in each individual region respectively with divisional measurement matrix to generate parts of samplings. Finally, regional samplings in all regions are transported directly to the sink for reconstruction. Subsequently, two issues for practical applications are considered. Experiments reveal that our scheme outperforms distributed CS, straight forward and the mixed scheme by comparing different parameters of the data package and the considered issues further guarantee its feasibility.
    Keywords: Regionalization Compressed Sensing; Transmission; Wireless Sensor Network.

  • Three Dimensional Power Efficient Distributed Node Localization in Wireless Sensor Networks   Order a copy of this article
    by Reza Shahbazian, Seyed Ali Ghorashi 
    Abstract: Wireless sensor networks are usually used in applications in which information is only applicable when the location of informative node is known. The localization algorithms used to determine node's location are performed in a centralized or distributed manner. Although the high accuracy is the main advantage of centralized algorithms, the distributed ones are more efficient in power consumption, robustness and reliability. In this paper, we first propose a three dimensional (3D) distributed node localization algorithm for wireless sensor networks in which sensor nodes cooperate to estimate the unknown location in a distribute manner. Then, we propose a node selection algorithm by switching off some sensor nodes causing a great reduction in the power consumption and extending the life time of the network. We further propose a weighting function to improve the performance of proposed algorithm by improving the localization accuracy. Simulation results confirm that proposed algorithms are applicable in 3D environments while achieving acceptable performance in case of localization error, improving the robustness and scalability of the network and reducing the power consumption at least by 20 percent.
    Keywords: Localization; Distributed; Wireless Sensor Network; Three Dimensional; Power Efficient; Node Selection; Weighing Function.

  • Distributed Constrained Optimization Over Cloud-Based Multi-Agent Networks   Order a copy of this article
    by Qing Ling 
    Abstract: We consider a distributed constrained optimization problem where a group of distributed agents are interconnected via a cloud center, and collaboratively minimize a network-wide objective function subject to local and global constraints. This paper devotes to developing efficient distributed algorithms that fully utilize the computation abilities of the cloud center and the agents, as well as avoid extensive communications between the cloud center and the agents. We address these issues by introducing two divide-and-conquer techniques, both of which assign the local objective functions and constraints to the agents while the global ones to the cloud center. The first algorithm is based on the celebrated alternating direction method of multipliers (ADMM) and the second one is a primal-dual first-order (PDFO) method. Both algorithms naturally yield two layers, the agent layer and therncloud center layer, which exchange intermediate variables so as to collaboratively obtain a network-wide optimal solution. However, the ADMM-based algorithm requires the cloud center and the agents to solve optimization subproblems at every iteration, and hence brings high computation cost. The PDFO method significantly reduces the iteration-wise computation cost by replacing the optimization subproblems with simple first-order gradient descent and projection operations. Both algorithms are proved to be convergent to the primal-dual optimal solution. Numerical experiments demonstrate the effectiveness of the proposed distributed constrained optimization algorithms.
    Keywords: Cloud computing; distributed optimization; alternating direction method of multipliers (ADMM); primal-dual first-order (PDFO) method.

  • An acquisition scheme for communications in multi-antenna sensor networks with low signal to noise ratio   Order a copy of this article
    by Joaquin Aldunate, Christian Oberli 
    Abstract: Recent results show that multiple antenna communications can improve the energy efficiency of wireless communications. These techniques are thus attractive for use in wireless sensor networks. In particular, diversity techniques can be used to improve the acquisition of wireless links, specially for low signal-to-noise ratio (SNR) situations. This paper presents an acquisition scheme well suited for wireless sensor networks such as low-power wide-area networks (LPWAN) with multiple antenna sensor nodes. The scheme exploits a differentially encoded preamble and receive diversity in order to detect signals at very low SNR without requiring channel state information. We show that it achieves a better trade-off between the probability of acquisition false alarm and failed acquisition than single-antenna communications. Therefore, it enables networks with larger node separation at given transmission power, such as in LPWANs. The scheme's performance is thoroughly analysed theoretically and verified by simulations.
    Keywords: multi-antenna; wireless sensor networks; acquisition scheme; preamble; low-power wide-area networks; low signal to noise ratio; packet-based wireless communications; preamble sequence; diversity; differential coding; channel state information; coherent combining; detector; receiver operating characteristic; probability of false alarm; signal detection.

  • An Intelligent Agent System for Managing Heterogeneous Sensors in Dispersed and Disparate Wireless Sensor Network Systems   Order a copy of this article
    by Yong Jin Lee, Jarrod Trevathan, Ian Atkinson, Wayne Read 
    Abstract: Wireless Sensor Network (WSN) systems typically employ middleware solutions to coordinate their various sensors and process their data. Middleware is also used to provide web services for storing/querying sensor network data. Any change in a WSN such as adding a new sensor or configuring existing sensors requires modification to its middleware and web service. This is problematic in a large-scale sensor observation system especially when multiple WSNs are deployed in different locations with heterogeneous sensors, and various middleware solutions and web service interfaces. To integrate hundreds of sensors with different capabilities through various middleware and web service specifications, a system needs to support all the encodings, models and services for registering, tasking and querying sensors. These characteristics are required to be pre-configured in order to use an appropriate function for a particular sensor. This paper presents an intelligent agent, which provides automatic semantic-based registration/configuration in a large-scale sensor observation system. The agent is developed using open source freely available technologies (e.g., Jena), and can react to any changes internally or externally made in WSNs (i.e., adding a new sensor or sending a task request to sensors/support systems). The agent makes a smart decision on which system function to use by integrating a semantic representation of sensor network data including middleware and web service specifications, and applying logical rules to the knowledge-base. We demonstrate how the agent operates using two real-world WSN systems. Each WSN is represented in RDF using a domain ontology, which extends the W3C SSN-XG ontology.
    Keywords: Wireless sensor networks; sensor web enablement; semantic technologies; SEMAT.

  • APRS : Adaptive Real-Time Payload Data Reduction Scheme for IoT/ WSN Sensor board with Multivariate Sensors   Order a copy of this article
    by NAYEF ALDUAIS, Jiwa Abdullah, Ansar Jamil 
    Abstract: In the applications of the Internet of Things (IoT) based on wireless sensor network (WSN), sensor board depends on battery that having a limited lifetime to function. Multivariate sensing boards pose additional challenges over the battery life time by additional data transmissions, thus draining the battery. In this paper, a new simple mechanism called as Adaptive Real-Time Payload Data Reduction Scheme (APRS) for energy-efficiency purpose is proposed. APRS aims to reduce the transmitted packet size for each sensed payload, moreover it prevents any transmissions if no significant change is reported by the payload sensing block. In the experiment, the APRS used a single variable to represent the row of the measured data (n-variables). It was based on the current relative difference and compared to the last measured data that had been transmitted to the fusion center. The APRS was able to reconstruct the original real-time sensed data (n-variables) from the representing variable at the fusion center. The performance of the APRS was evaluated through simulation by utilising various real-time environmental datasets. In addition, the APRS was successfully implemented in Libelium-Waspmote Gas sensor board for real-time IoT application. In conclusion, the APRS has managed to show its simplicity and flexibility for the real-time IoT/WSN application when it is compared with the other algorithms and its reduction ratio during a transmission is within acceptable range of 81 94 %. The average of the total percentage of energy saved by applied APRS in all nodes is 95%. Overall, the APRS has high performance in the reduction ratio of data and efficiency in energy consumption when it is compared with other recent multivariate data reduction methods.
    Keywords: WSN; IoT; multivariate data; Accuracy; Energy Consumption; data reduction.

  • Modified Greedy Perimeter Stateless Routing for Vehicular Ad hoc Networking Algorithm   Order a copy of this article
    by Tong Wang 
    Abstract: Vehicular Ad Hoc Networking (VANET) can connect vehicles and Road Side Units (RSUs) as self-organized networks. Thus, many routing protocols have been discussed to improve road security and collision avoidance. The purpose of VANET is to improve road safety and find a path in a well-mannered fashion, which is a priority in this field because driving is dangerous and casualties can occur. Many protocols have been proposed in the last several years for VANET. This paper proposes a modified Greedy Perimeter Stateless Routing (GPSR) protocol to improve the possibility of finding a path and compares it with other routing protocols such as Optimized Link State Routing (OLSR) and Ad Hoc On Demand Vector (AODV).
    Keywords: AODV; GPSR; OLSR; RSU; Road Security; VANET.

  • Lightweight and Practical Node Clustering Authentication Protocol for Hierarchical Wireless Sensor Networks   Order a copy of this article
    by Dengzhi Liu, Jian Shen, Anxi Wang, Chen Wang 
    Abstract: Hierarchical Wireless Sensor Networks(HWSNs) are used to provide real-time data and analysis of the monitoring area by the cooperation of low-cost nodes. The authentication towards multiple nodes and node cluster have become the research hots-pot considering of the requirement of application scenarios. There are many concerns about the sensitivity and privacy of data because the low-cost nodes are neither tamper-proof nor capable of performing public key cryptography efficiently. However, many researchers only focus on the existence of single node in the network, while the arrangement that multiple nodes attached to one cluster is out of consideration. In this paper, we propose a lightweight and practical node clustering authentication protocol for HWSNs. As we assume that one cluster to be authenticated is attached with a group of sensor nodes. The cluster head (CH) node takes full control of the entire authentication process in its cluster. In addition, the protocol is proved to offer enough security assurances and have resistance to various attacks under the security analysis. The regular operation of the network will not be affected or damaged by the incidents occurred during the authentication process.
    Keywords: Hierarchical Wireless Sensor Networks; Node Authentication; Lightweight; Practical.

  • STCS: A Practical Solar Radiation based Temperature Correction Scheme in Meteorological WSN   Order a copy of this article
    by Baowei Wang, Xiaodu Gu, Shuangshuang Yan 
    Abstract: In order to improve the timeliness, accuracy and availability of realtime meteorological data observation and promote the development of meteorological modernization, we use wireless sensor network to construct intelligent meteorological observation network to achieve fine observation data. But the accuracy of low-cost meteorological sensor is not high. In order to improve the accuracy of meteorological sensor network monitoring, some pioneer methods have been proposed. But the precision always cannot reach the ideal effect. In this article, we propose STCS (a solar radiation based air temperature error correction system). We did some pretreatments to the raw data set, including interpolation, time transformation. Then the relationship between solar radiation and temperature error is established by training GA-BP (Back propagation neural network optimized by genetic algorithm). At last, the trained neural network was applied to the temperature correction. Finally, we did smoothing process to the corrected data. Our results show that STCS achieves an average error of smaller than 0.34◦C. Consider to maximal absolute error, mean absolute error and standard deviation these three indicators, our results were improved by 14%, 6% and 12% respectively.
    Keywords: wireless sensor network; data correction; artificial neural network; solar radiation; meteorological observation.

  • K-Barrier Coverage in Wireless Sensor Networks Based on Immune Particle Swarm Optimization   Order a copy of this article
    by Yanhua Zhang, Xingming Sun, Zhanke Yu 
    Abstract: Barrier coverage of wireless sensor networks (WSNs) has been an interesting research issue for security applications. In order to increase the robustness of barriers coverage, k-barrier coverage is proposed to address this issue. In this paper, the k-barrier coverage problem is formulated as a global optimization problem solved by particle swarm optimization (PSO). However, the performance of PSO greatly depends on its parameters and it often suffers from being trapped in local optima. A novel particle swarm optimization program named AI-PSO (artificial immune-particle swarm optimization) is designed and the model of k-barrier coverage problem is proposed to solve this prob-lem. AI-PSO integrates the ability to exploit in PSO with the ability diversity maintenance mechanism of AI (artificial immune) to synthesize both algorithms strength. Simulation results show that the proposed algorithm is effective for the k-barrier coverage problems.
    Keywords: k-barrier coverage; particle swarm optimization; artificial immune; wireless sensor networks.

  • Home Appliances classification based on multi-feature using ELM   Order a copy of this article
    by Qi Liu, Fangpeng Chen, Fenghua Chen, Xiaodong Liu, Nigel Linge 
    Abstract: With the development of science and technology, the application in artificial intelligence has been more and more popular, as well as smart home has become a hot topic. And pattern recognition adapting to smart home attracts more attention, while the improvement of the accuracy of recognition is an important and difficult issue of smart home. In this paper, the characteristics of electrical appliances are extracted from the load curve of household appliances, and a fast and efficient home appliance recognition algorithm is proposed based on the advantage of classification of ELM (Extreme Learning Machine). At the same time, the sampling frequency with low rate is mentioned in this paper, which can obtain the required data through intelligent hardware directly, as well as reduce the cost of investment. And the intelligent hardware is designed by our team, which is wireless sensor network (WSN) composed by a lot of wireless sensors. Experiments in this paper show that the proposed method can accurately determine the using electrical appliances. And greatly improve the accuracy of identification, which can further improve the popularity of smart home.
    Keywords: Feature Extraction; Smart Home; Data Collection; WSN; ELM.; Smart Socket; Data analysis.

  • A Novel Meteorological Sensor Data Acquisition Approach Based on Unmanned Aerial Vehicle   Order a copy of this article
    by Chuanlong Li, Xingming Sun 
    Abstract: Meteorological sensor data acquisition is critical for various applications and researches. Currently, meteorological sensor data monitoring and acquisition mainly relies on the automatic weather station, wireless sensor network, satellites, and airborne remote sensing, etc. However, these conventional methods have some insuperable deficiencies. Recent advances in unmanned aerial vehicle for scientific use make drones easily overcome some of the paucity generated by these means. UAV (Unmanned Aerial Vehicle) as a sensor bearing platform can be used to collect sensor data in a more responsive, timely, three dimensional, and cost-effective manners. By implementing sensor network alike methods, drones can simulate the mobile ad-hoc networks in a mission and reduce the communication energy cost between each sensor node. This paper first demonstrates the feasibility of this approach, then proposes a sensor bearing framework aiming to bridge UAV remote sensing technique and customized meteorological sensor. A system prototype is developed and some real-world field tests indicate the application of the proposed framework is practical.
    Keywords: UAV; meteorological sensor; UAS; sensor data acquisition; remote sensing.