ESAM: Endocrine inspired Sensor Activation Mechanism for multi-target tracking in WSNs

Target tracking is one of the most important applications of wireless sensor networks. Optimized computation and energy dissipation are critical requirements to maximize the lifetime of the sensor network. There exists a demand for self-organizing and routing capabilities in the sensor network. Existing methods attempting to achieve these requirements, such as the LEACH-based algorithms, however, suffer either redundancy in data and sensor node deployment, or complex computation incurred in the sensor nodes. Those drawbacks result in energy use inefficiency and/or complex computation overhead. OCO, or Optimized Communication and Organization, is an algorithm that ensures maximum accuracy of target tracking, efficient energy dissipation, and low computation overhead on the sensor nodes. Simulation evaluations of OCO are compared with other two methods under various scenarios.

The rapid progress of wireless communication and embedded micro sensing technologies has made wireless sensor networks possible. Target tracking is an important application of wireless sensor networks. Good tracking quality and energy efficiency are the key requirements for any protocol designed for target tracking sensor networks. In this paper, we present a novel protocol, Adaptive Dynamic Cluster-based Tracking (ADCT), for tracking a mobile target. This protocol uses the optimal choice mechanism and dynamic cluster-based approach to achieve a good tracking quality and energy efficiency by optimally choosing the nodes that participate in tracking and minimizing the communication overhead, thus prolongs the lifetime of the whole sensor network. Simulation results show that our protocol can accurately track a target with random moving speeds and cost much less energy than other protocols for target tracking.

Monte Carlo Methods for Node Self-Localization and Nonlinear Target Tracking in Wireless Sensor Networks

Wireless Sensor Network (WSN) has many applications in day to day life. One of the applications of WSN is target tracking that uses sensors to track and localize the targets. This makes sensor node deployment in a network necessary and highly important. But the main challenge faced by sensor networks is the power consumption by sensor nodes. Hence an energy optimization technique must be in place that ultimately reduces the actual power consumption of the sensor nodes. Here, the shortest path algorithms are used in routing and it helps in reducing the energy consumption. The shortest path algorithms used in wireless sensor network are Dijkstra's algorithm and Floyd-Warshall's algorithm. They are also used for calculating throughput, packet delivery ratio and energy consumption for given number of nodes. The Floyd-Warshall's algorithm is not scalable and efficient for routing in WSN. Hence, we use modified Floyd-Warshall's algorithm that obtains better throughput, packet delivery ratio and minimized energy consumption. The new Modified Floyd-Warshall's algorithm calculates the shortest path from node to node by adding an acknowledgment mechanism. We have done a comparative analysis of Dijkstra's algorithm, Floyd-Warshall's algorithm, and modified Floyd-Warshall's algorithm for parameters like packet deliver ratio, throughput, and energy optimization for multiple nodes. From simulation results it is observed that the modified Floyd-Warshall's algorithm works better than Dijkstra's and Floyd Warshall's algorithm in terms of Packet Delivery ratio, throughput and energy consumption.

Secure and reliable object tracking in wireless sensor networks

Wireless sensor networks consist of a large number of low-cost, low-power, and multifunctional sensor nodes that communicate over short distances through wireless links. Such sensor networks are ideal candidates for a wide range of applications such as monitoring of critical infrastructures, data acquisition in hazardous environments, industry control systems, vehicular networks, and military operations. Wireless sensor networks introduce new security challenges due to their dynamic topology, severe resource constraints, and absence of a trusted infrastructure. The purpose of this special issue is to publish high-quality research papers as well as review articles addressing recent advances of wireless sensor network security. In this special issue, we will explore the topic of security challenges and solutions for the wide application of wireless sensor networks in different areas, such as RFID and smart grid. RFID has been widely used in logistics and internet of things. Smart grid leverages sensor networks to better balance the load of the power grid. Both of them have great impact on the daily life and areweak points of thewhole economy,which attract the attention of terrorists. The feasible attacks and defense solutions are still not clear.The papers in this volume also cover several important foundational security services for wireless sensor networks, such as key management, key distribution, secure cluster formation, secure architecture for multihop communication, intrusion prediction, and secure localization. All these foundational security services are critical bases for application of wireless sensor networks. We hope that the papers in this volume engender further thinking about new security challenges for wireless sensor networks and even further “out-of-the-box” ideas about how to solve new security problems for wireless sensor networks.

In recent years, a new wave of networks labelled Wireless Sensor Networks (WSNs) has attracted a lot of attention from researchers in both academic and industrial communities. A WSN consists of a collection of sensor nodes and a base station connected through wireless channels, and can be used for many applications such as military application, building distributed systems, physical environment monitoring, and security surveillance among others. A big advantage of sensor networks is represented by ease of deployment, reducing installation cost, possibility to distribute the tiny sensors over a wide region, and larger fault tolerance (V. Loscri et al., 2005). However, despite the infinite scopes of wireless sensor networks applications, they are limited by the node battery lifetime. Such constraints combined with a typical deployment of large number of sensor nodes have posed many challenges to the design and management of sensor networks and necessitate energyawareness at all layers of the networking protocol stack (Q. Xue & A. Ganz, 2004). Therefore, energy efficient algorithms have been one of the most challenging issues for WSNs. Sensor nodes can be in one of four states, namely transmit, receive, idle and sleep. The largest part of a node’s energy is consumed while transmitting and receiving. Minimizing the number of communications by eliminating or aggregating redundant sensed data saves much amount of energy (L. B. Ruiz et al., 2003). Among these clustering sensor networks are a very attractive approach because clustering allows for scalability, data aggregation, and energy efficiency. In a clustering network, nodes are grouped into clusters and there are special nodes called cluster head. They are responsible for an efficient way to lower energy consumption within a cluster by performing data aggregation. In a heterogeneous sensor network, two or more different types of nodes with different battery energy and functionality are used. On the other hand, in homogeneous networks all the sensor nodes are identical in terms of battery energy and hardware complexity. As a result, network performance decreases since the cluster head nodes goes down before other nodes do. Thus dynamic, energy efficient and adaptive cluster head selection algorithm is very important. Sensor networks can be divided in two classes as event-driven and continuous dissemination networks according to the periodicity of communication (L. B. Ruiz et al., 9

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .

Simultaneous localization and tracking (SLAT) in wireless sensor networks (WSNs) involves tracking the mobile target while calibrating the nearby sensor node locations. In practice, localization error propagation (EP) phenomenon will arise, due to the existence of the latest tracking error, target mobility, measurement error, and reference node location errors. In this case, the SLAT performance limits are crucial for the SLAT algorithm design and WSN deployment, and the study of localization EP principle is desirable. In this paper, we focus on the EP issues for the received signal strength-based SLAT scheme, where the measurement accuracy is assumed to be spatial-temporal-domain doubly random due to the target mobility, environment dynamics, and different surroundings at different reference nodes. First, the Cramer-Rao lower bound (CRLB) is derived to unveil both the target tracking EP and the node location calibration EP. In both cases, the EP principles turn out to be in a consistent form of the Ohm's Law in circuit theory. Second, the asymptotic CRLB analysis is then presented to reveal that both EP principles scale with the inverse of sensor node density. Meanwhile, it is shown that, the tracking and calibration accuracy only depends on the expectation of the measurement precision. Third, the convergence conditions, the convergence properties, and the balance state of the target tracking EP and the location calibration EP are examined to shed light on the EP characteristics of the SLAT scheme Finally, numerical simulations are presented to corroborate the EP analysis.

Monitoring and automatic control of building environment is a crucial application of Wireless Sensor Network (WSN) in which maximizing network lifetime is a key challenge. Previous research into the performance of a network in a building environment has been concerned with radio propagation within a single floor. We investigate the link quality distribution to obtain full coverage of signal strength in a four-storey building environment, experimentally. Our results indicate that the transitional region is of particular concern in wireless sensor network since it accommodates high variance unreliable links. The transitional region in a multi-storey building is mainly due to the presence of reinforced concrete slabs at each storey and the fac┬©ade which obstructs the radio signal and introduces an additional absorption term to the path loss.

With the advancement of technology, the application of Wireless Sensor Networks (WSNs) has increased in various fields, such as; military, medical and business. WSNs have the ability to control geographic areas and obtaining data and processing it in different environments. Sensor nodes independently sample local information and if necessary send this information to neighboring sensors and eventually send it to the well. These networks are independent and autonomous and humans have no interference in it. In particular, all nodes are identical, and in practice they work together to meet the overall purpose of the network. Due to inherent constraints in the resources and computing power of sensor nodes, security in WSNs has different challenges in comparison with security in traditional computer networks. Low-cost sensor networks allow the expansion of sensor groups in a variety of environments which are capable of operating in military fields and in urban areas. On the other hand, unreliable communication channels in many applications make it more difficult to provide information security in these networks. One of the common attacks in WSNs is a wormhole attack. In this paper, we will review and evaluate paper related to the wormhole attack.

An important application of wireless sensor networks is the tracking of objects moving through a monitored area. In some circumstances, a particle filter can perform substantially better than other tracking algorithms. A simple implementation is to transmit measurement data gathered at distributed sensors to a fusion centre and apply a single particle filter. The filter estimates the current position and predicts future locations so that appropriate sensors can be activated. This centralized approach can be energy-expensive and prone to failure: uncompressed data must be transmitted across multiple hops and there is a concentration of data transmission around the fusion site, which constitutes a single point of failure. This paper addresses these issues by proposing a distributed particle filter implementation in which parallel filters run at multiple nodes. These shared filters are used to quantize vectors of measurements. Simulations indicate that the scheme significantly reduces the energy expenditure of communication.

A Wireless sensor network (WSN) comprises several sensor nodes such as magnetic, thermal, and infrared, and the radar is set up in a particular geographical area. The primary aim of sensor network is to transmit reliable, secure data from one node to another node, node to base station and vice versa and from base station to all nodes in a network and to conserve the energy of sensor nodes. On the other hand, there are several restrictions such as large energy consumption, limited storage/memory and processing ability, higher latency, and insufficient resources. The related security issues in wireless sensor network are authenticity, confidentiality, robustness, integrity, and data freshness. The sensor nodes are susceptible to several attacks such as DOS, Sybil, flood, black hole, selective forwarding which results in the leakage of sensitive and valuable information. It is therefore necessary to provide security against these critical attacks in the network. Wireless sensor network were earlier used for military applications with the objective of monitoring friendly and opposing forces, battlefield surveillance, detection of attacks, but today Wireless Networking have a huge number of applications-environmental, healthcare, home, industrial, commercial and are still counting. This paper is an extensive review of the security requirements, attacks that are to be avoided and resolved for achieving a secure network connection. This paper also emphasizes various limitations and defense strategies to prevent threats and attacks. The issues of applications of wireless sensor network for smooth and reliable transmissions are also discussed. The sensor networks are popular for mission-critical-tasks and security is immensely required for such hostile environment employed networks.

Data gathering is a major function of many applications in wireless sensor networks. The most important issue in designing a data gathering algorithm is how to save energy of sensor nodes while meeting the requirements of special applications or users. Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many to one traffic pattern. These three characteristics can lead to severe packet collision, network congestion and packet loss, and even result in hot-spots of energy consumption thus causing premature death of sensor nodes and entire network. In this paper, we propose a load balance data gathering algorithm that classifies sensor nodes into different layers according to their distance to sink node and furthermore, divides the sense zone into several clusters. Routing trees are established between sensor node and sink depending on the energy metric and communication cost. For saving energy consumption, the target of data aggregation scheme is adopted as well. Analysis and simulation results show that the algorithm we proposed provides more uniform energy consumption among sensor nodes and can prolong the lifetime of sensor networks.

Maneuvering target tracking in wireless sensor networks (WSNs) has been a prominent research topic over the past twenty years. In many situations, WSNs are vulnerable to natural or man-made interference, resulting in uncertainty problems. In this paper, we propose an information-quality-based sensor selection method with estimation feedback for maneuvering target tracking in uncertain WSNs. First, based on the Generalized Pseudo-Bayesian estimator of first order (GPB1) and the unscented information filter (UIF), a GPB1-UIF algorithm with estimation feedback is presented. Inspired by the theory of information quality, an information-quality metric framework is proposed for sensor selection in uncertain WSNs. And the information-theoretic selection metrics are redesigned based on consistency measuring operator. Moreover, without knowing the number of selected sensors a priori, a multi-objective optimization problem is considered to determine the final selection strategy. Simulation results demonstrate that the proposed approach outperform the previous sensor selection methods.