Search

Many applications of wireless sensor networks (WSNs) require deploying sensors in hostile environments, where an adversary may eavesdrop communications. To secure communications in WSNs, the $q$ -composite key predistribution scheme has been proposed in the literature. In this paper, we investigate secure $k$ -connectivity in WSNs operating under the $q$ -composite scheme, in consideration of the unreliability of wireless links. Secure $k$ -connectivity ensures that any two sensors can find a path in between for secure communication, even when $k-1$ sensors fail. We present conditions on how to set the network parameters such that the network has secure $k$ -connectivity asymptotically almost surely. The result is given in the form of a sharp zero–one law. [ABSTRACT FROM AUTHOR]

In this paper, passive wireless sensor network technology is used to conduct in-depth research and analysis on the monitoring of the in-transit health status of railway transportation. Safety detection sensors, train communication networks, and other onboard devices organically constitute a train sensor network with comprehensive state sensing, information aggregation, and business collaboration. First, this paper analyzes the three-layer architecture of the sensing layer, network layer, and application layer of the train operation status safety detection sensor network. Based on analyzing the feasibility of Ethernet application in an onboard communication network, ring, multiring, and ladder-type sensor network structure schemes are designed. Next, the real-time performance and reliability of various sensor network structures are analyzed. First, the characteristics of bandwidth demand, priority, and importance of information transmission of each monitoring object are analyzed; then, the system utility function is established according to the bandwidth usage efficiency and communication demand of information transmission of each monitoring object; finally, the bandwidth allocation optimization model is solved by using a particle swarm optimization algorithm, and the remaining bandwidth resources are dynamically rationed on demand while ensuring the complete transmission of basic information of each monitoring object. Rail transit technology has profoundly affected and changed the travel and lifestyle of residents in the new era and will provide strong infrastructure support for the smooth advancement of new urbanization construction and development strategies. The remaining bandwidth resources are dynamically allocated on the premise of ensuring the complete transmission of basic information of each monitoring object. In summary, this paper presents a complete study on the optimal allocation of resources for wireless sensor networks dedicated to rail transit condition monitoring, starting from the perspectives of routing protocol optimization, data fusion rate optimization, and bandwidth dynamic allocation optimization to achieve the efficient use of limited resources. The achieved research results enrich the research content in the field of wireless monitoring of rail transit system conditions at home and abroad in a certain sense and will also provide theoretical and empirical support for practical practitioners, managers, and scholars of service condition monitoring of rail transit systems. [ABSTRACT FROM AUTHOR]

Mobile crowd sensing has emerged as a novel data collection paradigm by leveraging pervasive mobile sensing devices to enable various applications. To obtain good quality of service, incentive mechanisms are indispensable for attracting enough users. Most of the existing mechanisms focus on the offline scenario in which all users submit profiles in advance. However, the online scenario often appears in the real world wherein users arrive one by one in random order. In this paper, we investigate the frugal online incentive problem based on an online auction model, where users report their strategic profiles to the crowdsourcer in an online mode, and the crowdsourcer selects users before a deadline to complete a specific number of tasks while minimizing the total payment. We design two online mechanisms, namely, Frugal-OMZ and Frugal-OMG, satisfying computational efficiency, individual rationality, truthfulness, consumer sovereignty, and constant frugality under the zero arrival–departure interval model and the general interval model, respectively. Extensive simulations verify the desirable properties of our mechanisms. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for distributed target detection in wireless sensor networks (WSNs). Contrary to the conventional practice where every sensor uses an identical threshold for decision-making, an unequal and dynamic local sensor threshold selection scheme is proposed. This threshold selection scheme is based on a recently proposed statistical metric for multiple testing problems called the False Discovery Rate (FDR). Assuming a signal attenuation model, where the received signal power decays as the distance from the target increases, various performance indices like the system level probability of detection and the probability of false alarm are studied. Simulation results are provided to demonstrate the effectiveness of this approach. [ABSTRACT FROM AUTHOR]

This paper presents a cooperative, combinatorial search model for a multi-mobile sensor, multi-mobile target scenario in a two dimensional grid space. In the proposed model, sensors and targets act as searchers and hiders of a search game. A search game is a game between searcher and hider, modeled on a graph. In this paper, the identified problem states that multiple targets enter into a grid from the same or different sides and try to exit on the opposite directions of their respective entry sides. Alternatively, multiple mobile sensors are randomly deployed in the grid and try to maximize the number of target searched and to minimize search time before the targets leave the grid. This problem fits into several real life scenarios such as international border security, terrorist searching in a specified area, finding spies etc. The novelty of the proposed model is interpreting the problem as a search game and formulating strategies for the mobile sensors to optimize their moves to maximize the number of target searched and minimize search time. In this paper, shortest path and random walk strategies for the targets are analyzed by applying suitable mathematical models and on the other hand, advantages of cooperative over non-cooperative strategies for the mobile sensors are also shown with the help of analytical methods and simulation results. The significant mathematical concepts applied in the proposed model are as follows-computing shortest path, random walk, Markov chain, probability graph, overlapping of multiple probability graphs, cooperative and non-cooperative strategies etc. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) consist of networked sensor nodes, deployed to sense a phenomenon and report it to a base station. Sensor nodes are small and usually equipped with small batteries with limited capacity, and therefore, one of the most important design considerations for WSNs is power consumption. WSNs expend energy for communications, data processing and sensing; for commonly used RF communications this task accounts for the largest portion of power expended. Hybrid radio frequency/free space optical (RF/FSO) communications has been proposed to reduce power consumption by the sensor node, and in this paper, the performance of the RF/FSO WSN is compared against an RF-only WSN in terms of network lifetime and coverage. Results show that for the wide range of scenarios considered, the RF/FSO WSN lasts at least twice as long as its RF-only counterpart, despite providing the same level of network coverage. This paper also investigates network parameter selection for optimum RF/FSO network coverage. [ABSTRACT FROM AUTHOR]

The paper considers the connected target coverage (CTC) problem in wireless heterogeneous sensor networks (WHSNs) with multiple sensing units, termed MU-CTC problem. MU-CTC problem can be reduced to a connected set cover problem and further formulated as an integer linear programming (ILP) problem. However, the ILP problem is an NP-complete problem. Therefore, two distributed heuristic schemes, REFS (remaining energy first scheme) and EEFS (energy efficiency first scheme), are proposed. In REFS, each sensor considers its remaining energy and its neighbors' decisions to enable its sensing units and communication unit such that all targets can be covered for the required attributes and the sensed data can be delivered to the sink. The advantages of REFS are its simplicity and reduced communication overhead. However, to utilize sensors' energy efficiently, EEFS is proposed. A sensor in EEFS considers its contribution to the coverage and the connectivity to make a better decision. To our best knowledge, this paper is the first to consider target coverage and connectivity jointly for WHSNs with multiple sensing units. Simulation results show that REFS and EEFS can both prolong the network lifetime effectively. EEFS outperforms REFS in network lifetime, but REFS is simpler. [ABSTRACT FROM AUTHOR]

A wireless sensor network consists of many low-cost, low-power sensor nodes, which can perform sensing, simple computation, and transmission of sensed information. Long distance transmission by sensor nodes is not energy efficient since energy consumption is a superlinear function of the transmission distance. One approach to prolonging network lifetime while preserving network connectivity is to deploy a small number of costly, but more powerful, relay nodes whose main task is communication with other sensor or relay nodes. In this paper, we assume that sensor nodes have communication range r > 0, while relay nodes have communication range R ≥ r, and we study two versions of relay node placement problems. In the first version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting of relay and/or sensor nodes. In the second version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting solely of relay nodes. We present a polynomial time 7-approximation algorithm for the first problem and a polynomial time (5 + ϵ)-approximation algorithm for the second problem, where ϵ > 0 can be any given constant. [ABSTRACT FROM AUTHOR]

Recent advances in embedded microsensing technologies and low-energy cost sensors have made wireless sensor networks possible. Object tracking is an important research of wireless sensor networks. However, most object tracking tree is constructed based on a predefined mobility profile. When the real object movement behaviors are very different to the predefined mobility profile, the object tracking tree performance will become worse. In the paper, we will propose a dynamic adaptation mechanism, referred to as "Message-Tree Adaptive (MTA)" procedure, to improve the object tracking tree when the predefined mobility profiles do not match. From the simulation results, the performance of the object tracking tree can be significantly improved, when the MTA procedure is performed. [ABSTRACT FROM AUTHOR]

Energy hole problem is considered one of the most severe threats in wireless sensor networks. In this paper the idea of exploiting sink mobility for the purpose of culling the energy hole problem in hierarchical large-scale wireless sensor networks based on bees algorithm is presented. In the proposed scheme, a mobile sink equipped with a powerful transceiver and battery, traverses the entire field, and periodically gathers data from network cluster heads. The mobile sink follows an adaptive gathering strategy resilient to both connected and disconnected networks. The proposed gathering strategy geared to eliminate multihop relays required by all cluster heads to reach the mobile sink, balancing the traffic load across all network heads, meanwhile, reducing the loss that data may incur due to buffer overflow. Furthermore, enabling the mobile sink to navigate safely within cluttered and uncluttered fields augments the proposed gathering strategy. Extensive simulations are conducted in order to validate the effectiveness of the proposed strategy. The achieved results show an improvement in overall system performance compared to other mobility strategies. [ABSTRACT FROM AUTHOR]

RFID and Wireless Sensor Networks exemplify computationally constrained environments, where the compact nature of the components cannot support complex computations or high communication overhead. On the other hand, such components should support security applications such as message integrity, authentication, and time stamping. The latter are efficiently implemented by Hash Message Authentication Codes (HMAC). As clearly stated in the literature, current approved implementations of HMAC require resources that cannot be supported in constrained components. An approach to implement a compact HMAC by the use of stream ciphering is presented in this paper. [ABSTRACT FROM AUTHOR]

In this paper, a new framework for target tracking in a wireless sensor network using particle filters is proposed. Under this framework, the imperfect nature of the wireless i communication channels between sensors and the fusion center along with some physical layer design parameters of the network are incorporated in the tracking algorithm based on particle filters. We call this approach "channel-aware particle filtering." Channel-aware particle filtering schemes are derived for different wireless channel models and receiver architectures. Furthermore, we derive the posterior Cramér-Rao lower bounds (PCRLBs) for our proposed channel-aware particle filters. Simulation results are presented to demonstrate that the tracking performance of the channel-aware particle filters can reach their theoretical performance bounds even with relatively small number of sensors and they have superior performance compared to channel-unaware particle filters. [ABSTRACT FROM AUTHOR]

Recently, wireless sensor networks featuring direct sink access have been studied as an efficient architecture to gather and process data for numerous applications. In this paper, we focus on the joint effect of clustering and data correlation on the performance of such networks. More specifically, we propose a novel cluster-based data collection scheme for sensor networks with direct sink access (CDC-DSA) and provide an analytical framework to evaluate its performance in terms of energy consumption, latency, and robustness. In our scheme, cluster heads use a low-overhead and simple medium access control (MAC) conceptually similar to ALOHA to contend for the reachback channel to the data sink. Since, in our model, data is collected periodically, packet arrival is not modeled by a continuous random process, and therefore, we base our framework on a transient analysis rather than a steady-state analysis. Using random geometry tools, we study how the optimal average cluster size and energy savings, under the proposed MAC, vary according to the level of data correlation in the network. Extensive simulations for various protocol parameters show that our analysis is fairly accurate for a wide range of parameters. Our results suggest that, despite the trade-off between energy consumption and latency, both can be substantially reduced by a proper clustering design. [ABSTRACT FROM AUTHOR]

Many applications in wireless sensor networks re- quire sensor nodes to obtain their absolute or relative geographical positions. Although various localization algorithms have been recently proposed, most of them require nodes to be equipped with range-determining hardware to obtain distance information. In this paper, we propose a concentric anchor beacon (CAB) localization algorithm for wireless sensor networks. CAB is a range-free approach and uses a small number of anchor nodes. Each anchor emits beacons at different power levels. From the information received by each beacon heard, nodes can determine in which annular ring they are located within each anchor. Each node uses the approximated center of intersection of the rings as its position estimate. We also propose two heuristics, namely CAB with Equal Area and CAB with Equal Width, to determine the transmitting power levels of the beacons. Simulation results show that the estimation error is reduced by half when anchors transmit beacons at two different power levels instead of at a single power level. CAB also gives a lower estimation error than some other range-free localization schemes (e.g., Centroid and Approximated Point-In-Triangulation) when the anchor-to-node range ratio is less than 4. [ABSTRACT FROM AUTHOR]

This study focuses on the differences in power consumption between beam-forming and relaying data transmission methods in a sparse wireless ad-hoc network. These two methods are observed for the same parameters using an identical network topology in a simulation programme that was developed as a part of this study. This paper introduces the reader the background of sensor networks and exposes the aims of this study and methods used to simulate these networks. Finally, the results of a simulation are analysed and the two methods are compared, followed by the conclusion of the study and the project itself. [ABSTRACT FROM AUTHOR]

Emergency navigation systems for buildings and other built environments, such as sport arenas or shopping centres, typically rely on simple sensor networks to detect emergencies and, then, provide automatic signs to direct the evacuees. The major drawbacks of such static wireless sensor network (WSN)-based emergency navigation systems are the very limited computing capacity, which makes adaptivity very difficult, and the restricted battery power, due to the low cost of sensor nodes for unattended operation. If static wireless sensor networks and cloud-computing can be integrated, then intensive computations that are needed to determine optimal evacuation routes in the presence of time-varying hazards can be offloaded to the cloud, but the disadvantages of limited battery life-time at the client side, as well as the high likelihood of system malfunction during an emergency still remain. By making use of the powerful sensing ability of smart phones, which are increasingly ubiquitous, this paper presents a cloud-enabled indoor emergency navigation framework to direct evacuees in a coordinated fashion and to improve the reliability and resilience for both communication and localization. By combining social potential fields (SPF) and a cognitive packet network (CPN)-based algorithm, evacuees are guided to exits in dynamic loose clusters. Rather than relying on a conventional telecommunications infrastructure, we suggest an ad hoc cognitive packet network (AHCPN)-based protocol to adaptively search optimal communication routes between portable devices and the network egress nodes that provide access to cloud servers, in a manner that spares the remaining battery power of smart phones and minimizes the time latency. Experimental results through detailed simulations indicate that smart human motion and smart network management can increase the survival rate of evacuees and reduce the number of drained smart phones in an evacuation process. [ABSTRACT FROM AUTHOR]

Consider mobile targets in a plane and their movements being monitored by a network such as a field of sensors. We develop distributed algorithms for in-network tracking and range queries for aggregated data (for example, returning the number of targets within any user given region). Our scheme stores the target detection information locally in the network and answers a query by examining the perimeter of the given range. The cost of updating data about mobile targets is proportional to the target displacement. The key insight is to maintain in the sensor network a function with respect to the target detection data on the graph edges that is a differential form such that the integral of this form along any closed curve C gives the integral within the region bounded by C. The differential form has great flexibility, making it appropriate for tracking mobile targets. The basic range query can be used to find a nearby target or any given identifiable target with cost O(d), where d is the distance to the target in question. Dynamic insertion, deletion, coverage holes, and mobility of sensor nodes can be handled with only local operations, making the scheme suitable for a highly dynamic network. It is extremely robust and capable of tolerating errors in sensing and target localization. Targets do not need to be identified for the tracking, thus user privacy can be preserved. In this paper, we only elaborate the advantages of differential forms in tracking of mobile targets. Similar routines can be applied for organizing many other types of information—for example, streaming scalar sensor data (such as temperature data field)—to support efficient range queries. We demonstrate through analysis and simulations that this scheme compares favorably to existing schemes that use location services for answering aggregate range queries of target detection data. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are more likely to be distributed asynchronous systems. In this paper, we investigate the achievable data collection capacity of realistic distributed asynchronous WSNs. Our main contributions include five aspects. First, to avoid data transmission interference, we derive an \cal R0-proper carrier-sensing range (\cal R0-PCR) under the generalized physical interference model, where \cal R0 is the satisfied threshold of data receiving rate. Taking \cal R0-PCR as its carrier-sensing range, any sensor node can initiate a data transmission with a guaranteed data receiving rate. Second, based on \cal R0-PCR, we propose a Distributed Data Collection (DDC) algorithm with fairness consideration. Theoretical analysis of DDC surprisingly shows that its achievable network capacity is order-optimal and independent of network size. Thus, DDC is scalable. Third, we discuss how to apply \cal R0-PCR to the distributed data aggregation problem and propose a Distributed Data Aggregation (DDA) algorithm. The delay performance of DDA is also analyzed. Fourth, to be more general, we study the delay and capacity of DDC and DDA under the Poisson node distribution model. The analysis demonstrates that DDC is also scalable and order-optimal under the Poisson distribution model. Finally, we conduct extensive simulations to validate the performance of DDC and DDA. [ABSTRACT FROM AUTHOR]

Increasing the lifetime of a wireless sensor network (WSN) while maintaining good coverage is a well studied research problem. A cellular automaton is a biologically inspired model that has been widely used to model different physical systems including wireless sensor networks. In this paper, we use cellular automaton algorithms to optimize the coverage and the lifetime of a WSN. An advantage of the cellular automaton model is that its algorithms rely only on limited local information that can easily be stored in individual nodes. We consider a radius 2 neighborhood instead of a radius 1 neighborhood and consider different energy levels for different operations of the network. We compare different rules of this model with the rules of the existing model (radius 1 neighborhood) and we devise a probabilistic technique to solve the sudden falls of the coverage in these models. We develop cellular automaton based algorithms also for the object detection problem and present simulation results. [ABSTRACT FROM AUTHOR]

This paper examines the impact of sensor censoring on the decision fusion performance in networks with an unknown number of sensors. In performing the decision fusion process, the fusion center applies the Chair-Varshney test; suitably modified to take account of the unknown network size. A closed-form analytical expression is derived for the error probability of the modified fusion rule. It is shown that reducing the censoring probability, i.e., allowing a greater number of sensors to transmit their decisions, does not necessarily improve the decision fusion performance. Rather, there exists a certain censoring probability threshold below which increasing the number of transmitting sensors simply incurs a greater intra-network communication overhead but without improving the global decision performance. Our findings establish that the design of energy-efficient local detection rules should commence with the censoring rate threshold. Hence, it is desirable that the value of this censoring probability threshold be known in advance. Accordingly, the present study proposes an efficient method for identifying the censoring probability threshold value and determining the corresponding local censoring rule. [ABSTRACT FROM AUTHOR]

Exploiting high density features of wireless sensor networks represents a challenging issue. In this context, anonymous, asynchronous and randomly distributed sensors are considered along with few devices, called actors, which are more powerful than sensors in terms of energy and transmission capabilities. The paper proposes a new distributed training protocol for coarse-grain localization purposes in high density environments. The aim is to auto-organize the sensors with respect to a virtual infrastructure centered at actors and constituted of concentric rings divided into sectors. Analytical study as well as experiments on the proposed protocol are provided. The obtained results show under which theoretical and practical settings the training process can be performed in a fast and high quality way with respect to the granularity of the required localization and the energy consumption. [ABSTRACT FROM AUTHOR]

In time-critical wireless sensor network (WSN) applications, a high degree of reliability is commonly required. A dynamical jumping real-time fault-tolerant routing protocol (DMRF) is proposed in this paper. Each node utilizes the remaining transmission time of the data packets and the state of the forwarding candidate node set to dynamically choose the next hop. Once node failure, network congestion or void region occurs, the transmission mode will switch to jumping transmission mode, which can reduce the transmission time delay, guaranteeing the data packets to be sent to the destination node within the specified time limit. By using feedback mechanism, each node dynamically adjusts the jumping probabilities to increase the ratio of successful transmission. Simulation results show that DMRF can not only efficiently reduce the effects of failure nodes, congestion and void region, but also yield higher ratio of successful transmission, smaller transmission delay and reduced number of control packets. [ABSTRACT FROM AUTHOR]

Data generated in wireless sensor networks may not all be alike: some data may be more important than others and hence may have different delivery requirements. In this paper, we address differentiated data delivery in the presence of congestion in wireless sensor networks. We propose a class of algorithms that enforce differentiated routing based on the congested areas of a network and data priority. The basic protocol, called Congestion-Aware Routing (CAR), discovers the congested zone of the network that exists between high-priority data sources and the data sink and, using simple forwarding rules, dedicates this portion of the network to forwarding primarily high-priority traffic. Since CAR requires some overhead for establishing the high-priority routing zone, it is unsuitable for highly mobile data sources. To accommodate these, we define MAC-Enhanced CAR (MCAR), which includes MAC-layer enhancements and a protocol for forming high-priority paths on the fly for each burst of data. MCAR effectively handles the mobility of high-priority data sources, at the expense of degrading the performance of low-priority traffic. We present extensive simulation results for CAR and MCAR, and an implementation of MCAR on a 48-node testbed. [ABSTRACT FROM AUTHOR]

With the advance of sensing technologies and their applications, advanced sensor networks are gaining increasing interest. For certain sensitive applications, heterogeneous sensors can be deployed in the monitored space to ensure scalability, high-speed communication, and long network lifetime. Hybrid sensor networks have capabilities to combine the use of both resource-rich and resource-impoverished sensor nodes. This paper proposes a heterogeneous broadband sensor network architecture for military vehicle tracking. Powerful sensor devices with good bandwidth and energy capabilities are used as a communication backbone while energy sensors are used to track moving targets. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

IEEE 802.15.4 is a new standard that addresses the need of low-rate wireless personal area networks or LR-WPAN with a focus on enabling pervasive wireless sensor networks for residential, commercial and industrial applications. The standard is characterized by maintaining a high level of simplicity, allowing for low cost and low power implementations. This paper presents a brief technical introduction of the IEEE 802.15.4 standard and analyzes its applicability for building automation applications. [ABSTRACT FROM AUTHOR]

Locationing problem in Wireless Sensor Networks(WSNs) can be viewed as a general distributed sensor problem. It is with sensors that can discover other nodes or estimate ranges between nodes, that serve as position references. In this paper, we show that sensors acquire coarse-grain location awareness by the training protocol. The training protocol which hybrids the synchronization and training procedure. In this protocol, synchronization and training are combined into one scheme. The sink node sends two beacons in each slot instead of one. In the training, sensor searching for its location using a binary search scheme. Our simulation results shown less number of cycles needed for training. [ABSTRACT FROM AUTHOR]

The use of wireless technologies in the field of agriculture, or so-called smart or precision agriculture, is considered as one of the main efforts applied nowadays to multiply the food production on earth. However, wireless sensor network (WSN) technology is still at its early development stage and its application in agriculture and food industry is still rare due to the lack of farmers' awareness and outreach about the matter. This paper presents a new agro-sensor named AgriLogger with an aim to collect, store for long periods and transmit agrometeorological data represented by temperature and relative humidity in remote areas hard to reach and not served by telecommunication networks. The sensor exhibits long battery life, in the order of 10 years, thanks to low consumption technologies and to hardware sleep/wake up approach. It can be remotely placed on preselected sites through a customized drone. This latter, equipped with a dedicated payload, can then return on the sites where sensors have been placed, and, while hovering, wakes up the single devices and uploads their collected data through local wireless network. Field tests have demonstrated that the sensor, after being placed manually in two different positions, inside and outside a vineyard canopy, is able to collect and store successfully agrometeorological data like temperature and relative humidity. Moreover, the use of a drone potentially allows the collection of data from remote areas and, therefore, is able to provide a periodical monitoring of agro-ecological conditions. [ABSTRACT FROM AUTHOR]

Wireless sensors operating in harsh environments have the potential to be error-prone. This paper presents a distributive model-based diagnosis algorithm that identifies nonlinear sensor faults. The diagnosis algorithm has advantages over existing fault diagnosis methods such as centralized model-based and distributive model-free methods. An algorithm is presented for detecting common non-linearity faults without using reference sensors. The study introduces a model-based fault diagnosis framework that is implemented within a pair of wireless sensors. The detection of sensor nonlinearities is shown to be equivalent to solving the largest empty rectangle (LER) problem, given a set of features extracted from an analysis of sensor outputs. A low-complexity algorithm that gives an approximate solution to the LER problem is proposed for embedment in resource constrained wireless sensors. By solving the LER problem, sensors corrupted by non-linearity faults can be isolated and identified. Extensive analysis evaluates the performance of the proposed algorithm through simulation. [ABSTRACT FROM AUTHOR]

In the modern technological world, there are several key factors in the construction of sensor networks. These include maximizing the coverage and minimizing the cost of the network. Like any information system, the sensor network must also meet the conditions of survivability. This is why the development of a method for assessing the survivability of the sensor network is also a key factor. The purpose of this study is to develop a method to establish the maximum coverage of the territory of the sensor network at minimum cost with the ability to assess the survivability of the network. Coverage maximization while minimizing the network's cost is achieved by finding the optimal pair of values of the coverage radius and the level of the intersection of coverage areas. These values are found by solving a nonlinear multicriteria optimization problem with the use of the genetic algorithm. The designed method for estimating the survivability of sensor networks takes into account not only the importance of network components but also the bandwidth of the network elements. The result of using the proposed methods is a set of Pareto optimal pairs of values of the radii of coverage and the value of the intersection of the coverage areas. In the case of network survivability assessment, the result, in addition to the percentage assessment, is a set of vulnerable sensors and network communication channels. The proposed network survivability estimation method improved the estimation accuracy by 18% compared to methods used in previous works. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks are used in situations where it becomes difficult to deploy and utilize networks with fixed infrastructure. Group Management within such network is an important challenge which is considered as a fundamental objective of such deployment. A good number of schemes have been proposed as a solution to this problem in the existing literature; however it is a well known fact that none of the existing schemes has fully addressed the group management issues. We have proposed a novel mechanism known as Cluster Based Group Management Scheme for Wireless Sensor Networks. Cluster Based Group Management Scheme (CBGMS) adopts an intermediate path in between the known solutions and additional novel features. It is important to mention that CBGMS not only provide a comprehensive Group Management solution but also addresses some of the known inter-related issues of Wireless Sensor Networks which is presented and explained in this paper. [ABSTRACT FROM AUTHOR]

Abstract: A wireless sensor network is composed of a large number of sensor nodes that are densely deployed in a sensing environment. The effectiveness of the wireless sensor networks depends to a large extent on the coverage provided by the sensor deployment scheme. In this paper, we present a sensor deployment scheme based on glowworm swarm optimization (GSO) to enhance the coverage after an initial random deployment of the sensors. Each sensor node is considered as individual glowworms emitting a luminant substance called luciferin and the intensity of the luciferin is dependent on the distance between the sensor node and its neighboring sensors. A sensor node is attracted towards its neighbors having lower intensity of luciferin and decides to move towards one of them. In this way, the coverage of the sensing field is maximized as the sensor nodes tend to move towards the region having lower sensor density. Simulation results show that our GSO-based sensor deployment approach can provide high coverage with limited movement of the sensor nodes. [Copyright &y& Elsevier]

A wireless sensor network consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. Different approaches have used for simulation and modeling of SN (Sensor Network) and WSN. Traditional approaches consist of various simulation tools based on different languages such as C, C++ and Java. In this paper, MATLAB (7.6) Simulink was used to build a complete WSN system. Simulation procedure includes building the hardware architecture of the transmitting nodes, modeling both the communication channel and the receiving master node architecture. Bluetooth was chosen to undertake the physical layer communication with respect to different channel parameters (i.e., Signal to Noise ratio, Attenuation and Interference). The simulation model was examined using different topologies under various conditions and numerous results were collected. This new simulation methodology proves the ability of the Simulink MATLAB to be a useful and flexible approach to study the effect of different physical layer parameters on the performance of wireless sensor networks [ABSTRACT FROM AUTHOR]

Currently, it is rapidly increasing convergence services based on various mobile devices with sensors like Smart Home. Specifically the mobility of the sensors in Smart Home merged with wireless sensor networks (WSN) brings security issues such as re-authentication and tracing the node movement. We extend our novel and efficient node authentication and key exchange protocol that support Irregular distribution. Compared with previous protocols, our protocol has only a third of communication and computational overhead. We expect our protocol to be the efficient solution that increases the lifetime of sensor network. [ABSTRACT FROM AUTHOR]

The reliability of wireless sensor networks (WSN) is getting increasing importance as this kind of networks are becoming the communication base for many cyber-physical systems (CPS). Such systems rely on sensor data correctness to make decisions; therefore, faulty data can lead such systems to take wrong actions. Errors can be originated by sensor's hardware failures or software bugs and also from the intentional interference of intruders. The gateways that connect such WSN to the Internet are natural intruders' targets as they usually run conventional operating systems and communication protocols. This work proposes a confidence attribution scheme, based on lightweight predictors running on the sensors. The solution also proposes a parameterizable formula, in order to stamp every value sent by a sensor with a confidence level, calculated upon the values of a subset of correlated sensors. This work also presents an algorithm that can identify a defective sensor into its subset. The use of predictors and confidence attribution are proposed as the basis of a mechanism that increases the WSN resilience against sensor failure or bad data injection by intruders. Several simulations were performed to evaluate the detection efficiency against different types of sensor errors. This work also analyses mechanisms to deal with concept drifts in the WSN lifetime. [ABSTRACT FROM AUTHOR]

Analysis of finite wireless networks is a fundamental problem in the area of wireless networking. Today, due to the vast amount of literature on large-scale wireless networks, we have a fair understanding of the asymptotic behavior of such networks. However, in real world we have to face finite networks for which the asymptotic results cease to be valid. We refer to networks as being finite when the number of nodes is less than a few hundred. Here we study a model of wireless networks, represented by random geometric graphs. In order to address a wide class of the network's properties, we study the threshold phenomena. Being extensively studied in the asymptotic case, the threshold phenomena occurs when a graph theoretic property (such as connectivity) of the network experiences rapid changes over a specific interval of the underlying parameter. Here, we find an upper bound for the threshold width of finite line networks represented by random geometric graphs. These bounds hold for all monotone properties of such networks. We then turn our attention to an important non-monotone characteristic of line networks which is the Medium Access (MAC) layer capacity, i.e. the maximum number of possible concurrent transmissions. Towards this goal, we provide a linear time algorithm which finds a maximal set of concurrent non-interfering transmissions and further derive lower and upper bounds for the cardinality of the set. Using simulations, we show that these bounds serve as reasonable estimates for the actual value of the MAC-layer capacity. [ABSTRACT FROM PUBLISHER]

Target tracking is one application of wireless sensor networks and energy efficient target tracking algorithms that can be used for accurate tracking are highly desired. In order to achieve energy savings, we focus on reducing energy usage by limiting the number of sensors used to track a target through monitoring their data quality and by limiting the amount of data being sent to the cluster head. We propose an energy efficient target tracking protocol that uses two algorithms to accomplish this goal. Simulation studies show that the network lifetime is extended up to 35% with application of both algorithms and that the side effect on target tracking accuracy is not too negative. [ABSTRACT FROM AUTHOR]

We propose a scheme for rate-constrained distributed nonparametric regression using a wireless sensor network. The scheme is universal across a wide range of sensor noise models, including unbounded and nonadditive noise; it has low complexity, requiring simple operations such as uniform scalar quantization with dither and message passing between neighboring nodes in the network, and attains minimax optimality for regression functions in common smoothness classes. We present theoretical results on the tradeoff between the compression rate, communication complexity of encoding, and the MSE and demonstrate empirical performance of the scheme using simulations. [ABSTRACT FROM AUTHOR]

Bootstrapping secure communication among sensor nodes deployed in hostile environments is an important and challenging problem. A common approach to solve this problem is to use a key pre-distribution scheme in which each sensor node is assigned a subset of keys selected from some key pool. The resilience of a key pre-distribution scheme depends on the size of the key pool that the scheme uses for distributing keys among sensor nodes. After deployment, if two sensor nodes are within communication range of one and other, and share at least one common key, then they can establish a secure channel using the common key. We show that, when the key distribution is near-uniform, the maximum size of a key pool that can be used by any key pre-distribution scheme is upper-bounded by s²/p where s is the amount of space available on a sensor node for storing keys and p is the probability that two sensor nodes share a common key. We define the utilization factor of a key pre-distribution scheme to measure how effective the scheme is in using the largest key pool available at its disposal for fixed values of s and p. We explore the effect of the utilization factor of a scheme on its resilience. [ABSTRACT FROM AUTHOR]

Event detection is a crucial task for wireless sensor network applications, especially environment monitoring. Existing approaches for event detection are mainly based on some predefined threshold values and, thus, are often inaccurate and incapable of capturing complex events. For example, in coal mine monitoring scenarios, gas leakage or water osmosis can hardly be described by the overrun of specified attribute thresholds but some complex pattern in the full-scale view of the environmental data. To address this issue, we propose a nonthreshold-based approach for the real 3D sensor monitoring environment. We employ energy-efficient methods to collect a time series of data maps from the sensor network and detect complex events through matching the gathered data to spatiotemporal data patterns. Finally, we conduct trace-driven simulations to prove the efficacy and efficiency of this approach on detecting events of complex phenomena from real-life records. [ABSTRACT FROM AUTHOR]