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Wireless Body Area Network (WBAN) is a small-scaled sensor network consisting of a series of medical devices attributed to, around, or implanted in a human body, providing continuous monitoring by different sensors to collect vital signals or motion and GPS. This paper proposes an effective routing algorithm to balance the energy consumption within a WBAN in order to prolong the overall lifetime of the network, called dynamic routing algorithm (DRA) and its improved version based on a multipath choice mechanism. Theoretical analysis and simulation result are demonstrated to evaluate the performance of the algorithm and represent that energy consumption of sensors in the network is reasonably scheduled and life cycle of the network is significantly extended. The routing algorithm proposed in this paper may be potentially applied to significantly save energy of multiple types of sensors during vital signals aggregating and transmitting under the WBAN. [ABSTRACT FROM AUTHOR]

This paper presents an integrated modeling method providing superior Quality of Service (QoS) for wireless sensor networks (WSNs) which is suitable for smart distribution grid (SDG) communication. Traditional QoS model based on IEEE802.15.4 protocol cannot meet the communication requirements of multipriority data in smart distribution grid. In order to meet the specification of power system communication, a new QoS-enabled medium access control (MAC) model based on unfair competition channel access mechanism (UCCAM) is developed in this paper. The proposed model can ensure that the communication system of WSN provides different Qualities of Service for different priority data. According to different requirements for the communication time, the data of SDG are divided into three types: high priority, middle priority, and low priority data. The state transition of buffering queue data in node is described by a three-dimensional Markov chain model. Delay time, effective throughput rate, and channel collision rate models are developed, respectively, to evaluate communication performance of WSN applied in smart distribution grid. The simulation results show that the proposed model can provide different Qualities of Service for different priority data and is more efficient than the IEEE802.15.4e standard and the traditional methods. [ABSTRACT FROM AUTHOR]

In smart home, location estimation based on PIR sensors is very popular. Existing methods by various sensors technologies and intelligent algorithms are used to achieve a high accuracy. In fact, how to deploy the PIR sensor is directly related to the accuracy. In this paper, we present an approach to deploying the PIR sensor based on the accessible priority by genetic algorithm. This paper presents a genetic algorithm that searches for an optimal or near optimal solution to the PIR sensor deployment for smart home. The fitness function of GA is based on the accessible priority of indoor areas. The accessible priority value of different area is set according to the indoor environment and daily accessible habits. The performance of the genetic algorithm was evaluated using several metrics, and the simulation results demonstrated that the proposed algorithm can optimize the network coverage in terms of accessible frequency. [ABSTRACT FROM AUTHOR]

An accurate localization algorithm tailored for anisotropic wireless sensors networks (WSNs) is proposed in this paper. Using the proposed algorithm, each regular or position-unaware node estimates its distances only to reliable anchors or position-aware nodes. The latter are properly chosen following a new reliable anchor selection strategy that ensures an accurate distance estimation making thereby our localization algorithm more precise. It is shown that the proposed algorithm is implementable in both 2-dimensional (2D) and 3-dimensional (3D) scenarios. A power saving mechanism aiming to enhance the WSN lifetime is also envisaged in this paper. It is proven that the proposed algorithm could easily incorporate such a mechanism. Simulations show that our algorithm, whether combined or not with the power saving mechanism, consistently outperforms the best representative localization algorithms currently available in the literature in terms of accuracy, even with the presence of nonuniform node distribution or radiation irregularities. [ABSTRACT FROM AUTHOR]

Wireless signal can be easily influenced by the environment in the propagation process. The signal propagation model is the most appropriate model for current indoor environment to ensure the ranging accuracy based on received signal strength indicator (RSSI). In this paper, we propose a robust localization algorithm based on the RSSI ranging scope by which the RSSI ranging error caused by using a fixed parameter in signal propagation model is dramatically eliminated. Our contributions in this paper are twofold. First, the influence of RSSI ranging error on positioning accuracy is well discussed in detail in the scope of the wireless signal propagation model. Second, we develop a robust localization algorithm which creates a one-to-one mapping between the RSSI value and the distance scope based on the value scope of path loss exponent in the signal propagation model. Simulation results indicate that the proposed localization algorithm based on the RSSI ranging scope is robust under different environments, when the real path loss exponent is difficult to measure accurately. [ABSTRACT FROM AUTHOR]

Time reversal (TR), which leads various multipath signals to focus spatiotemporally on arbitrarily complex propagation environments, can resist signal multipath delay and attenuation which is caused by inhomogeneous complex environments. In this paper, the windowed time reversal (WTR) method for distance measurement between the wireless sensor network (WSN) nodes is proposed based on TR. In the WTR, the main lobe of the channel response is captured by a window. WTR not only takes advantage of the spatiotemporal focus features of TR, but also compensates the multipath effect to eliminate various factors from the environment. WTR can recover the favorable symmetry of the main lobe of channel response, thereby accurately measuring the times-of-arrival (TOA) of the electromagnetic wave and distance between WSN nodes. By analyzing the characteristics of the time reversal operator, the theoretical basis of the WTR is given in this paper. An algorithm for node distance measurement with WTR in indoor environments is described and a large number of simulations with various environments are carried out. The errors for the proposed WTR have been analyzed. Simulation results show that ranging errors by WTR are less than 1% no matter how many obstacles are in the indoor environment. [ABSTRACT FROM AUTHOR]

This paper proposes and describes a trust model for distributed systems based on groups of peers. A group is denned as a collection of entities with particular affinities and capabilities. All entities may have a trust and a reputation value of each other in the system. In many cases it may be necessary to trust the whole system instead of one particular entity. In such cases group trust represents the trust of their particular members. To achieve this, this paper presents a group trust calculation model. We implemented the proposed model in a P2P simulation tool and presented main results for group trust calculation. [ABSTRACT FROM AUTHOR]

Most routing algorithms in delay tolerant networks (DTN) need nodes serving as relays for the source to carry and forward message. Due to the impact of selfishness, nodes have no incentive to stay in the network after getting message (e.g., free riders). To make them be cooperative at specific time, the source has to pay certain reward to them. In addition, the reward may be varying with time. On the other hand, the source can obtain certain benefit if the destination gets message timely. This paper considers the optimal incentive policy to get the best trade-off between the benefit and expenditure of the source for the first time. To cope with this problem, it first proposes a theoretical framework, which can be used to evaluate the trade-off under different incentive policies. Then, based on the framework, it explores the optimal control problem through Pontryagin's maximum principle and proves that the optimal policy conforms to the threshold form in certain cases. Simulations based on both synthetic and real motion traces show the accuracy of the framework. Through extensive numerical results, this paper demonstrates that the optimal policy obtained above is the best. [ABSTRACT FROM AUTHOR]

This paper discusses a node selection problem for bearings-only tracking in wireless sensor networks (WSNs). Saving energy and prolonging the lifetime of the network are the research focuses due to the severely constrained resource of WSNs. An energy efficient network management strategy is necessary to achieve good tracking performance at low cost. In this paper, an energy efficient node selection algorithm for bearings-only sensors in decentralized sensor networks is proposed. The residual energy of a node is incorporated into the objective function of node selection. A new criterion of node selection is also made to coordinate with the objective function. Compared with the other common methods, the proposed method can reduce the cost of the entire network, balance nodes energy expenditure, and extend the lifetime of network. Simulation results prove the effectiveness of the proposed method and show good performance in tracking accuracy and energy consumption. [ABSTRACT FROM AUTHOR]

To prolong the network lifetime, various scheduling approaches that schedule wireless devices of nodes to switch between active and sleep states have been studied. Topology control schemes are one of the scheduling approaches that can extend the network lifetime and reduce the additional communication delays at the same time. However, they do not guarantee that all nodes have the same lifetime. They reduce the network coverage and prevent seamless communications. This paper proposes an adaptive duty-cycling (ADC) scheme to solve the unbalanced energy consumption generated from the conventional topology control schemes. Our scheme can be applied as a subprocess of them and enable well-balanced energy consumption among all nodes by applying a different duty-cycle to each group based on group size. Therefore, ADC scheme reduces the coverage reduction and maintains the communication delay as a constant throughout the network lifetime. Simulation results show that our scheme extends the network lifetime by at least 25%. This paper also proposes t-ADC scheme. It can be more effectively applied to various environments by adjusting the duty-cycle determined by the ADC scheme which is based on the network traffic amount. We show that t-ADC scheme prolongs the lifetime up to 17% compared to ADC scheme in a low traffic network. [ABSTRACT FROM AUTHOR]

This paper considers the problem of estimating the clock bias and the position of an unknown source using time of arrival (TOA) measurements obtained at a sensor array to achieve time synchronization and source localization. The study starts with deriving the localization mean square error (MSE) for the case where we pretend that the source clock bias is absent and apply TOA positioning to find the source position. An upper bound on the clock bias, over which we shall obtain a higher localization MSE than that from jointly identifying the clock bias with the source position, is established. Motivated by the MSE analysis, this paper proceeds to develop a new efficient solution for joint synchronization and source localization. The new method is in closed-form, computationally attractive, and more importantly; it is shown analytically to attain the CRLB accuracy under small Gaussian TOA measurement noise. Computer simulations are conducted to corroborate the theoretical development and illustrate the good performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper considers the problem of estimating the clock bias and the position of an unknown source using time of arrival (TOA) measurements obtained at a sensor array to achieve time synchronization and source localization. The study starts with deriving the localization mean square error (MSE) for the case where we pretend that the source clock bias is absent and apply TOA positioning to find the source position. An upper bound on the clock bias, over which we shall obtain a higher localization MSE than that from jointly identifying the clock bias with the source position, is established. Motivated by the MSE analysis, this paper proceeds to develop a new efficient solution for joint synchronization and source localization. The new method is in closed-form, computationally attractive, and more importantly; it is shown analytically to attain the CRLB accuracy under small Gaussian TOA measurement noise. Computer simulations are conducted to corroborate the theoretical development and illustrate the good performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Big data and distributed computing are of great importance in wireless sensor networks (WSNs).They are always bonded together, and the latter one upholds the former one. In distributed computing, mobile agent model is the mainstream technology. With autonomy, communicativeness, mobility, and role, mobile agent model is more suitable for large-scale, resources-restrained WSN to deal with big data. This paper mainly studies migration schemes for mobile agents, determines core factors of migration strategy, and proposes SMLA and DMLA algorithms. And aiming at revealing the characteristics of target tracking, this paper puts forward pid-DMLA algorithm; and considering multiple agents' cooperation, it presents Mpid-DMLA algorithm. Moreover, this paper evaluates and analyzes the advantages and disadvantages of the above-mentioned four algorithms by simulations. [ABSTRACT FROM AUTHOR]

Combining individual sensor decisions can be an effective way for the enhancement of the final decision on sensor fields for intruder detection. This paper proposes a novel methodology to unify the decisions from individual sensors on a sensor field through the (hidden Markov model) HMM and rules. The HMM especially provides a stochastic decision out of the individual sensor decisions on the sensor field; then it is filtered through rule inferences reflecting the knowledge of movement patterns on the level of the sensor field, such as spatial-temporal information and factual information on the movement of objects. This use of contextual knowledge remarkably improves the final decision for the detection. Also, this paper proposes the discretization method to express the state space of sensor field, and the performance evaluation is given by simulations. [ABSTRACT FROM AUTHOR]

Recently, wireless sensor networks (WSNs) technologies have been utilized in diverse domains. Areas where WSNs are applied have been expanded from industries, schools, and research institutes to all fields of the human society. However,WSNs should be fixed or flexible depending on the areas of application and monitoring situations. Furthermore, measures for the security of data sensed when sensor nodes communicate with each other are not perfect, so sensors are sometimes easily attacked, and the security measures cover neither cases where sensors receive wrong information nor cases where attacks on external sensor nodes are sensed. Therefore, this paper provides the GML that can be mapped on actual topography so that optimum coverage can be inferred and can set target areas for two situations: mobile sensor networks (MSNs) and fixed sensor networks (FSNs). Sensors can be efficiently arranged through this sensor node information, and when the sensors have been arranged, security simulation functions applied with data encryption for data transmission between sensor nodes are provided. This paper also proposes an external detection trace simulator (EDTS) that would make sensing data transmitted between sensors visually provide information on the sensing of external attacks. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) consist of thousands of nodes that need to communicate with each other. However, it is possible that some nodes are isolated from other nodes due to limited communication range. This paper focuses on the influence of communication range on the probability that all nodes are connected under two conditions, respectively: (1) all nodes have the same communication range, and (2) communication range of each node is a random variable. In the former case, this work proves that, for 0 < ε < e_1, if the probability of the network being connected is 0.36ε, by means of increasing communication range by constant C(ε), the probability of network being connected is at least 1 - ε. Explicit function C(ε) is given. It turns out that, once the network is connected, it also makes the WSNs resilient against nodes failure. In the latter case, this paper proposes that the network connection probability is modeled as Cox process. The change of network connection probability with respect to distribution parameters and resilience performance is presented. Finally, a method to decide the distribution parameters of node communication range in order to satisfy a given network connection probability is developed. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of group behavior recognition. Our approach is to merge all the possible features of group behavior (individuals, groups, relationships between individuals, relationships between groups, etc.) with static context information relating to particular domains. All this information is represented as a set of features by classification algorithms. This is a very high-dimensional problem, with which classification algorithms are unable cope. For this reason, this paper also presents four feature selection alternatives: two wrappers and two filters. We present and compare the results of each method in the basketball domain. [ABSTRACT FROM AUTHOR]

This paper addresses the localization of a timing signal source based on the time of arrival (TOA) measurements that are collected from nearby sensors that are position known and synchronized to each other. Generally speaking, for such TOA-based source localization, the corresponding observation equations contain nonlinear relationship between measurements and unknown parameters, which normally results in the nonexistence of any efficient unbiased estimator that attains the Cramer-Rao lower bound (CRLB). In this paper, we devise a new approach that utilizes linearization and adopts suitable coordinate system translation to eliminate nonlinearity from the converted observation equations. The performance analysis and simulation study conducted show that our proposed algorithm can achieve the CRLB when the zero-mean Gaussian and independent measurement errors are sufficiently small. [ABSTRACT FROM AUTHOR]

Recently, machine-to-machine (M2M) communication has been studied in the single cell system. However, in the multicell system multiple M2M type devices at the edge of a cell may suffer from the strong interference that consists of the intercell interference from other cells and the intracell interference from other M2M devices in the local cell. In this paper, we study the relay beamforming strategy to guarantee the quality of service (QoS) requirements of the multiple destination devices in multicell systems. We minimize the transmit power of the base stations (BSs) and relays to save the power of M2M devices, while guaranteeing the receive signal-to-interference-and-noise ratio (SINR) of the destination devices. The main contribution of this paper is that we propose an iterative algorithm to jointly optimize the BS and relay beamforming weights with minimizing the BS and relay power under the receive SINR constraints in the perfect channel state information (CSI). Using the semidefinite relaxation (SDR) technology, the optimization problems for the BS and relay beamforming weights can be effectively solved. In addition, we also discuss the issue of imperfect CSI in practice. Simulation results validate our theoretical analysis and demonstrate that our proposed iterative scheme can achieve near-optimal performance within a few iterations. [ABSTRACT FROM AUTHOR]

A novel circle fitting algorithm is proposed in this paper. The key points of this paper are given as follows: (i) it formulates the circle fitting problem into the special source localization one in wireless sensor networks (WSN); (ii) the multidimensional scaling (MDS) analysis is applied to the data points, and thus the propagator-like method is proposed to represent the circle center parameters as the functions of the circle radius; (iii) the virtual source localization model can be rerepresented as special nonlinear equations of a unique variable (the circle radius) rather than the original three ones (the circle center and radius), and thus the classical fixed-point iteration algorithm is applied to determine the radius and the circle center parameters. The effectiveness of the proposed circle fitting approach is demonstrated using the simulation and experimental results. [ABSTRACT FROM AUTHOR]

Routing and spectrum allocation is an important challenge in cognitive wireless mesh networks. A distributed routing and spectrum allocation algorithm with cooperation (DRSAC-W) in cognitive wireless mesh networks is proposed in this paper. In order to show the decrease of the average end-to-end delay with cooperation in DRSAC-W, a distributed routing and spectrum allocation algorithm without cooperation (DRSAC-WO) is proposed in this paper. Minimizing the average end-to-end delay is the objective of DRSAC-W and DRSAC-WO. Simulation results show that the proposed algorithm DRSAC-W with cooperation can alleviate the high delay due to the heterogeneity of available channels of different nodes and achieve low average end-to-end delay. [ABSTRACT FROM AUTHOR]

Navigation with wireless sensor networks (WSNs) is the key to provide an effective path for the mobile node. Without any location information, the path planning algorithm generates a big challenge. Many algorithms provided efficient paths based on tracking sensor nodes which forms a competitive method. However, most previous works have overlooked the distance cost of the path. In this paper, the problem is how to obtain a path with minimum distance cost and effectively organize the network to ensure the availability of this path. We first present a distributed algorithm to construct a path planning infrastructure by uniting the neighbors' information of each sensor node into an improved connected dominating set. Then, a path planning algorithm is proposed which could produce a path with its length at most c times the shortest Euclidean length from initial position to destination. We prove that the distributed algorithm has low time and message complexity and c is no more than a constant. Under different deployed environments, extensive simulations evaluate the effectiveness of our work. The results show that factor c is within the upper bound proved in this paper and our distributed algorithm achieves a smaller infrastructure size. [ABSTRACT FROM AUTHOR]

IEEE 802.16j is an amendment to the IEEE 802.16 broadband wireless access standard to enable the operation of multihop relay stations (RSs). It aims to enhance the coverage, per user throughput of IEEE 802.16e. Comparing with a base station (BS), RS does not need a wireline backhaul and has much lower hardware complexity. Moreover, using RSs can significantly reduce the deployment cost of the system. Unfortunately, there are some tradeoffs in the case of multi-hop RSs. Subscriber stations (SSs), located in a long distance, are suffered from the bottleneck of multi-hop, throughput degradation, and increasing of end-to-end delay. This paper proposes a network coding-based relay scheme for multi-hop relay networks, called NC-BR. It allows RSs to combine two wireless backhaul transmissions into one using the network coding technique. This paper also proposes an improved OFDMA frame structure design for the multi-hop relay network. This technique provides higher utilization for the relay zone by reorganizing the RSs transmission sequence. The analysis and simulation results confirm that the proposed scheme can enhance the throughput gain up to 140% and reduce the end-to-end delay by up to 83%. The simulation results also show that the proposed scheme can reduce the jitter by up to 58%. [ABSTRACT FROM AUTHOR]

Recently, underwater wireless sensor networks (UWSNs) have attracted much research attention from both academia and industry, in order to explore the vast underwater environment. UWSNs have peculiar characteristics; that is, they have large propagation delay, high error rate, low bandwidth, and limited energy. Therefore, designing network/routing protocols for UWSNs is very challenging. Also, in UWSNs, improving the energy efficiency is one of the most important issues since the replacement of the batteries of underwater sensor nodes is very expensive due to the unpleasant underwater environment. In this paper, we therefore propose an energy efficient routing protocol, named (energy-efficient depth-based routing protocol) EEDBR for UWSNs. EEDBR utilizes the depth of sensor nodes for forwarding data packets. Furthermore, the residual energy of sensor nodes is also taken into account in order to improve the network lifetime. Based on the comprehensive simulation using NS2, we observe that EEDBR contributes to the performance improvements in terms of the network lifetime, energy consumption, and end-to-end delay. A previous version of this paper was accepted in AST-2011 conference. [ABSTRACT FROM AUTHOR]

This paper considers the localization problem in mobile sensor networks. Such a problem is a challenging task, especially when measurements exchanged between sensors may contain outliers, that is, data not matching the observation model. This paper proposes two algorithms robust to outliers. These algorithms perform a set-membership estimation, where only the maximal number of outliers is required to be known. Using these algorithms, estimates consist of sets of boxes whose union surely contains the correct location of the sensor, provided that the considered hypotheses are satisfied. This paper proposes as well a technique for evaluating the number of outliers to be robust to. In order to corroborate the efficiency of both algorithms, a comparison of their performances is performed in simulations using Matlab. [ABSTRACT FROM AUTHOR]

Power assignment in wireless ad hoc networks is an important issue of topology control which assigns power for each wireless node so that the induced communication graph satisfies some desired properties such as the connectivity and the energy spanner. In this paper, we study the problem of power assignment in order that its induced communication graph meets the following properties: (1) it is an energy-t-spanner which is energy efficient; (2) it is k-fault resistant which can withstand up to k - 1 node failures where k⩾1; (3) the interference is minimal. We propose algorithms to address this problem. Both the theoretic analysis and the simulations in the paper prove that our algorithms can induce a k-fault resistant energy spanner and furthermore the interference is minimized. To the best of our knowledge, this is the first paper to study the power assignment problem simultaneously considering spanner properties, the fault tolerance, and the interference reduction. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are tightly linked with the practical environment in which the sensors are deployed. Sensor positioning is a pivotal part of main location-dependent applications that utilize sensornets. The global topology of the network is important to both sensor network applications and the implementation of networking functionalities. This paper studies the topology discovery with an emphasis on boundary recognition in a sensor network. A large mass of sensor nodes are supposed to scatter in a geometric region, with nearby nodes communicating with each other directly. This paper is thus designed to detect the holes in the topological architecture of sensornets only by connectivity information. Existent edges determination methods hold the high costs as assumptions. Without the help of a large amount of uniformly deployed seed nodes, those schemes fail in anisotropic WSNs with possible holes. To address this issue, we propose a solution, named PPA based on Poincare-Perelman Theorem, to judge whether there are holes in WSNs-monitored areas. Our solution can properly detect holes on the topological surfaces and connect them into meaningful boundary cycles. The judging method has also been rigorously proved to be appropriate for continuous geometric domains as well as discrete domains. Extensive simulations have been shown that the algorithm even enables networks with low density to produce good results. [ABSTRACT FROM AUTHOR]

Data gathering is one of the most important operations in many wireless sensor networks (WSNs) applications. In order to implement data gathering, a tree structure rooted at the sink is usually defined. In most wireless sensor networks, nodes are powered by batteries with limited energy. Prolonging network lifetime is a critical issue for WSNs. As a technique for signal processing, compressed sensing (CS) is being increasingly applied to wireless sensor networks for saving energy. Compressive sensing can reduce the number of data transmissions and balance the traffic load throughout networks. In this paper, we investigate data gathering in wireless sensor networks using CS and aim at constructing a maximum-lifetime data-gathering tree. The lifetime of the network is defined as the number of data-gathering rounds until the first node depletes its energy. Based on the hybrid-CS data-gathering model, we first construct an arbitrary data-gathering tree and then use the random switching decision and optimal parent node selecting strategy to adjust the load of the bottleneck node and prolong the network lifetime. Simulation results show that the proposed algorithm outperforms several existing approaches in terms of network lifetime. [ABSTRACT FROM AUTHOR]

Underwater acoustic sensor networks (UWASNs) are effective tools for exploring and observing the ocean. Due to the nonnegligible physical restrictions of the underwater acoustic communication, most MAC protocols applied in the existing terrestrial wireless networks become inapplicable. In this paper, we propose a multiple handshaking MAC protocol for UWASNs called multihandshaking MAC (MHM). Using the method of multiple handshaking and competitive mechanism of control packets, our protocol is proposed to make the contending nodes share the underwater acoustic channel much more fairly and more efficiently. The main idea of MHM is to allow multiple nodes to transmit and receive data packets at the same time without packet collisions. We also propose a competitive mechanism of control packets, which can guarantee that there will not be data collisions in the process of multiple packet transmissions. Simulation results show that our protocol can achieve better performance, including throughput, delay, and fairness. [ABSTRACT FROM AUTHOR]

The average symbol error probability (ASEP) and outage probability (OP) performance of mobile-to-mobile (M2M) senor networks employing transmit antenna selection (TAS) and selection combining (SC) over N-Nakagami fading channels are investigated in this paper. Based on the moment generating function (MGF) approach, the exact ASEP expressions are derived for several modulation schemes. The exact closed-form OP expressions are also presented. Then, the ASEP and OP performance under different conditions are evaluated through numerical simulations to confirm the accuracy of the analysis. The simulation results show that the number of antennas, the fading coefficient, and the number of cascaded components have an important influence on the ASEP and OP performance. [ABSTRACT FROM AUTHOR]

It is a great challenge for wireless sensor network to provide enough information for targets localization due to the limits on application environment and its nature, such as energy, communication, and sensing precision. In this paper, a multiple targets localization algorithm with sparse information (MTLSI) was proposed using compressive sensing theory, which can provide targets position with incomplete or sparse localization information. It does not depend on extra hardware measurements. Only targets number detected by sensors is needed in the algorithm. The monitoring region was divided into a plurality of small grids. Sensors and targets are randomly dropped in grids. Targets position information is defined as a sparse vector; the number of targets detected by sensor nodes is expressed as the product of measurement matrix, sparse matrix, and sparse vector in compressive sensing theory. Targets are localized with the sparse signal reconstruction. In order to investigate MTLSI performance, BP and OMP are applied to recover targets localization. Simulation results show that MTLSI can provide satisfied targets localization in wireless sensor networks application with less data bits transmission compared to multiple targets localization using compressive sensing based on received signal strengths (MTLCS-RSS), which has the same computation complexity as MTLIS. [ABSTRACT FROM AUTHOR]

Demand response (DR) is a major contributor to grid stabilization during peak times. As the scope and functions of DR increase, DR participation of residential customers has attracted great attention. The main issue of DR design for the residential sector is to build an integrated network for exchange of DR signals between the utility operator and home users who want to participate in DR services at various locations. In this paper, we introduce an automated residential DR model based on advanced metering infrastructure (AMI) network. The internationally recognized standard protocol, known as the open automated demand response version 2.0 (OpenADR 2.0), is applied to realize a fully automated DR (ADR). In order to utilize existing AMI devices as ADR resources, the smart meter is modified while retaining current structure and functions, and various ADR devices are developed based on OpenADR 2.0 protocol. Simulation and demonstration tests are conducted to confirm conformance of the protocol and to verify load variations of home appliances under our ADR model. The developed software programs have obtained an international certification from the OpenADR Alliance. [ABSTRACT FROM AUTHOR]

Energy saving in wireless sensor networks is a fundamental issue as most sensor nodes are powered by batteries. The deployment of mobile sinks can alleviate the imbalance of energy consumption among sensor nodes, thereby prolonging the network lifetime. In this paper, we study the energy management problem in sensor networks, using multiple mobile sinks. We first formulate the problem as a novel data collection problem and then propose an efficient algorithm for it. The key challenge in the design of the proposed algorithm is how to balance the workload among mobile sinks and the energy consumption among sensor nodes through the control of the movement of mobile sinks. We finally evaluate the performance of the proposed algorithm through experimental simulation. Experimental results show that the proposed algorithm is very promising, which can improve the energy efficiency and the quality of data transmission in the sensor network significantly. [ABSTRACT FROM AUTHOR]

Traffic anomaly detection is emerging as a necessary component as wireless networks gain popularity. In this paper, based on the improved Autoregressive Integrated Moving Average (ARIMA) model, we propose a traffic anomaly detection algorithm for wireless sensor networks (WSNs) which considers the particular imbalanced, nonstationary properties of the WSN traffic and the limited energy and computing capacity of the wireless sensors at the same time. We systematically analyze the characteristics of WSN traffic, the causes of WSN abnormal traffic, and the latest related research and development. Specifically, we improve the traditional time series ARIMA model to make traffic prediction and judge the traffic anomaly in a WSN. Simulated and real WSN traffic data gathered from University of North Carolina are used to carry out simulations on Matlab. Simulation results and comparative analyses demonstrate that our proposed WSN traffic anomaly detection scheme has better anomaly detection accuracy than traditional traffic anomaly detection algorithms. [ABSTRACT FROM AUTHOR]

Sink location protection is critical to the viability of sensor networks as the central point of failure. Most existing work related to sink location protection focuses on local traffic analysis attack. In this paper, we study the sink location protection problem under a more powerful type of attack, the global traffic analysis attack. In order to hide the sink location, a protocol based on packet sending rate adjustment (SRA) is proposed. By controlling the packet sending rate of each node according to the current number of source nodes, SRA conceals the real traffic volume generated by source nodes and hence disguises the location of the sink. For further reducing the communication cost, we propose a light weight SRA protocol (L-SRA), which protects the sink location while significantly decreasing the communication cost. Performance of both SRA and L-SRA has been validated by theoretical analysis and simulation results. [ABSTRACT FROM AUTHOR]

A wireless sensor network (WSN) model by analyzing the limitations of existing localization algorithm is proposed in this paper. Specifically, neither the anchor nor the ID is required in the proposed model, and the node function is limited. The hardware function of the node in our model is independent of the MAC protocol. Moreover, based on the proposed WSN model, we design an energy efficient anchor-free localization algorithm for no-identity WSN. Instead of multiple measurements, mathematical calculation is adopted to acquire the position information. Subsequently, the effectiveness of the algorithm is confirmed by rigid theory. The simulation results show that the proposed algorithm can improve the performance of localization and energy efficiency in WSN significantly. [ABSTRACT FROM AUTHOR]

In recent years, wireless sensor networks have been widely employed in monitoring agriculture. With social development, large-scale agriculture monitoring by satellite sensor network attracts increasing concerns as well as the transmission problem of plentiful agriculture data. In this paper, we propose a new method of constrained route based on the metric of delay and capacity (CR-MDC) to find route path in satellite sensor network, with the aim of achieving congestion avoidance of network for transferring a large amount of data while monitoring large-scale agriculture. We model the rosette constellation network according to network characteristics through a discrete-time figure and formulate the scheme as a binary integer programming problem in consideration of time-variant parameters, for example, link capacity and link delay. The performance of the constrained route algorithm is compared with the Dijkstra-based routing protocols proposed in existing literature. Moreover, an improved CR-MDC under a route similarity constraint is developed to reduce the handoff times in adjacent slots. Simulation results show that the proposed scheme exhibits lower blocking probability and maximum link utilization but higher average network delay than Dijkstra-based routing while the improved CR-MDC has a higher route similarity than CR-MDC. [ABSTRACT FROM AUTHOR]

Network architecture analysis is a curial issue for a large scale Machine-To-Machine (M2M) network. Considering an M2M backbone network which consists of distributed satellite clusters in geosynchronous orbit (GEO), a new distributed satellite cluster network (DSCN) hybrid topology architecture is proposed in this paper. To the best of the authors’ knowledge, the conceptions of domains, strong/weak link, hubs, small world, and degree realizability are proposed for the first time in the DSCN based M2M backbone networks. How these features affect the network is given through analysis and simulation. By employing Network Science Theory, a strong constraint DSCN topology is presented. In addition, we compare the DSCN with several typical network topologies. Results show that the proposed hybrid architecture realizes a stunning trade-off between the efficiency and robustness. [ABSTRACT FROM AUTHOR]

Wormhole attack is one of the severe threats to wireless sensor and ad hoc networks. Most of the existing countermeasures either require specialized hardware or demand high network overheads in order to capture the specific symptoms induced by the wormholes, which in result limits their applicability. In this paper, we exploit an inevitable symptom of wormholes and present Pworm, a passive wormhole detection and localization system based upon the key observation that a large amount of network traffic will be attracted by the wormholes. The proposed scheme is passive, real-time, and efficient against both active and passive wormholes. Our approach silently observes the variations in network topology to infer the wormhole existence and solely relies on network routing information. It does not necessitate specialized hardware or poses rigorous assumptions on network features. We evaluate our scheme through extensive simulations of 100 to 800 nodes for various network scales and show that Pworm is well suited for false alarms, scalability, and time delay in terms of activation as well as detection latencies. [ABSTRACT FROM AUTHOR]

Data collection from deployed sensor networks can be with static sink, ground-based mobile sink, or Unmanned Aerial Vehicle (UAV) based mobile aerial data collector. Considering the large-scale sensor networks and peculiarity of the deployed environments, aerial data collection based on controllable UAV has more advantages. In this paper, we have designed a basic framework for aerial data collection, which includes the following five components: deployment of networks, nodes positioning, anchor points searching, fast path planning for UAV, and data collection from network. We have identified the key challenges in each of them and have proposed efficient solutions. This includes proposal of a Fast Path Planning with Rules (FPPWR) algorithm based on grid division, to increase the efficiency of path planning, while guaranteeing the length of the path to be relatively short. We have designed and implemented a simulation platform for aerial data collection from sensor networks and have validated performance efficiency of the proposed framework based on the following parameters: time consumption of the aerial data collection, flight path distance, and volume of collected data. [ABSTRACT FROM AUTHOR]

Backpressure based scheduling has revealed remarkable performance in wireless multihop networks as reported in a lot of previous work. However, its lack of consideration on energy use efficiency is still an obstacle for backpressure based algorithms to be deployed in resource-constrained wireless sensor networks (WSNs). In this paper, we focus on studying the design of energy efficient backpressure based algorithm. For this purpose, we propose a gradient-assisted energy-efficient backpressure scheduling algorithm (GRAPE) for WSNs. GRAPE introduces a new link-weight calculation method, based on which gradient information and nodal residual energy are taken into account when making decisions on backpressure based transmission scheduling. According to the decisions made by this new method, packets are encouraged to be forwarded to nodes with more residual energy. We theoretically prove the throughput-optimality of GRAPE. Simulation results demonstrate that GRAPE can achieve significant performance improvements in terms of energy use efficiency, network throughput, and packet delivery ratio as compared with existing work. [ABSTRACT FROM AUTHOR]

The effect of climate change and human activities leads to a series of dangerous phenomena, such as landslides and flood. In such a context, building a system to monitor environmental hazards is seriously needed. Some studies propose to use wireless sensor network (WSN) technique for landslide monitoring systems. Two important factors for these systems are the flexibility and the energy management. This paper focuses on the development of a flexible and efficient WSN for detecting rainfall-induced landslides. A flexible switching between star and tree topologies is used to adapt to weather conditions in order to maximize the reliability of the transmission. Moreover, the power management is designed concurrently with the weather condition to improve both the operation reliability and the power efficiency. The performance of our designed WSN is evaluated by both simulation and outdoor experiment. Detailed calculation of the power budget is presented thoughtfully to confirm the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

The On-Demand Multicast Routing Protocol (ODMRP) is a multicast routing protocol for mobile ad hoc networks (MANETs). Its efficiency, simplicity, and robustness against mobility render it one of the most widely used MANET multicast protocols. In this paper, we present an Adaptive On-Demand Multicast Routing Protocol (A-ODMRP), an improved version of ODMRP. ODMRP lacks a control mechanism for the physical layer. Nodes in ODMRP transmit multicast data at a fixed transmission rate and power level for the physical layer. Also, as the number of nodes belonging to the forwarding group increases, there is significant packet drop or retransmission due to interference between the nodes that send multicast data. However, A-ODMRP implements an adaptive control mechanism with a cross-layer algorithm for the physical layer. When a node transmits multicast data, A-ODMRP can adjust the transmission rate and power level of the physical layer to minimize packet drop or retransmission due to interference between nodes belonging to the forwarding group. Simulation results confirmed that A-ODMRP provides an improved goodput of up to 42% compared to ODMRP. [ABSTRACT FROM AUTHOR]

Gas source localization (GSL) is a critical component in wireless sensor network (WSN) which can be used to estimate the position of gas leaks through the gas concentration measured by the monitoring nodes. In this paper, we first derive a gas diffusion model under windy conditions based on the gas diffusion theory. Because of the nonlinearity of the gas diffusion model under windy conditions, the traditional weighted centroid algorithm for gas source localization produces very inaccurate estimation of the source location. To address this problem, we propose a novel gas source localization algorithm which combines the weighted centroid method and particle filter. Simulation results validate the effectiveness of our algorithm under unknown gas source strength. Compared to weighted centroid method alone, our algorithm shows a higher accuracy in location. Moreover, its convergence rate is improved by the preestimation of initial value. [ABSTRACT FROM AUTHOR]

More recently, an increasing number of object-attached sensors are publishing their real-time state on the Internet by using state-of-the-art Web technologies, which make the sensor search service extremely important for the Web of Things (WoT). However, the existing issues that the sensor search service is facing bring huge challenges to the design of matching state estimation scheme. In this paper, an architecture of high-efficiency content-based sensor search system is depicted to provide a prototype system for sensor search. And then a matching state estimation scheme is proposed in detail, including a sensor state prediction approach to accurately estimate future sensor readings and a match estimating and verifying approach to effectively classify and verify candidate sensors, in order to enhance the performance of our search system. Simulation results show that our matching state estimation scheme dramatically reduces the communication overhead of search system and achieves excellent performance in terms of recall ratio and precision ratio. [ABSTRACT FROM AUTHOR]

Underwater acoustic communication channel is time varying and has Doppler effect due to wind, sea surface roughness, and platform motion. We have to recognize the changing channel state and apply it to communication technique for increasing transmission efficiency in the underwater acoustic channel. In this paper, we propose more reliable Doppler estimation method based on frequency average and remodulation. We conducted the simulation and sea trial to evaluate the performance of the proposed method. When the channel coding technique was not applied, the uncoded bit error rate performance of the proposed method was improved about maximum 50.3% compared with conventional method. [ABSTRACT FROM AUTHOR]

With the rapid development of wireless sensor networks (WSNs), the security of WSNs is an important issue in this field because of their vulnerabilities to attacks. Designing a reasonable trust management scheme that can evaluate the trust relationships among sensor nodes accurately is a challenging but meaningful task. In this paper, a credible Bayesian-based trust management scheme (BTMS) is proposed. The overall trust value is aggregated by both direct and indirect trust information. The former is calculated by a modified Bayesian equation and updated by a sliding window. The latter is computed by recommendations from a third party. Moreover, the indirect trust computation is invoked conditionally according to the uncertainty of direct trust calculated via Entropy Theory and malicious feedbacks are excluded. Meanwhile, different recommendations are appropriately weighted in light of the trust levels of recommenders. Simulations are conducted and the results show that, compared with existing approaches, the proposed trust model performs better in defeating attacks. [ABSTRACT FROM AUTHOR]

Cognitive radio networks (CRNs) are an emerging wireless communications technique for resolving the significant spectrum scarcity problem. Despite their promising characteristics, CRNs also introduce new security threats, especially the internal attacks during the spectrum sensing and allocation process, which can degrade the efficiency of spectrum sensing and allocation. To address this issue, this paper proposes a distributed secure cooperative spectrum sensing strategy (DSCS) based on a dynamic reputation model to defend against attacks and provide reliable spectrum sensing. Moreover, the reputation values are used as weights in a novel distributed cheat-proof spectrum allocation strategy (DCSA) based on the Vickrey-Clarke-Groves (VCG) mechanism. Both theoretical analysis and simulation results indicate that the proposed DSCS and DCSA strategies can provide an effective countermeasure against the internal spectrum sensing data falsification (SSDF) attacks through enabling secondary users to obtain more accurate cooperative sensing results in adversarial environments. [ABSTRACT FROM AUTHOR]

We address the problem of DOA estimation in positioning of nodes in wireless sensor networks. The Stochastic Maximum Likelihood (SML) algorithm is adopted in this paper. The SML algorithm is well-known for its high resolution of DOA estimation. However, its computational complexity is very high because multidimensional nonlinear optimization problem is usually involved. To reduce the computational complexity of SML estimation, we do the following work. (1) We point out the problems of conventional SML criterion and explain why and how these problems happen. (2) A local AM search method is proposed which could be used to find the local solution near/around the initial value. (3) We propose an algorithm which uses the local AM search method together with the estimation of DML or MUSIC as initial value to find the solution of SML. Simulation results are shown to demonstrate the effectiveness and efficiency of the proposed algorithms. In particular, the algorithm which uses the local AM method and estimation of MUSIC as initial value has much higher resolution and comparable computational complexity to MUSIC. [ABSTRACT FROM AUTHOR]

This paper uses the concept of effective transmission coverage area as a model for the derivation of analytic expressions in order to characterize the dynamic statistics of link lifetime, new link arrival rate, new link interarrival time, link breakage interarrival time, and so forth. Extensive simulations have been undertaken to verify the derived analytical expressions via generated mobility traces. Results demonstrate that the proposed analytical model can characterize the dynamic statistics well. Furthermore, the mathematical results of expected link life and expected new link arrival rate are provided to be used in analyzing the network connectivity. Combining with queueing theory, the upper bound connectivity of a VANET is obtained. This work thus provides a fundamental guideline on designing new mobility models, new routing protocols, and the corresponding performance analysis in VANET. [ABSTRACT FROM AUTHOR]