Stationary and Mobile Target Detection using Mobile Wireless Sensor Networks

In this work, we study the target detection and tracking problem in mobile sensor networks, where the performance metrics of interest are probability of detection and tracking coverage, when the target can be stationary or mobile and its duration is finite. We propose a physical coverage-based mobility model, where the mobile sensor nodes move such that the overlap between the covered areas by different mobile nodes is small. It is shown that for stationary target scenario the proposed mobility model can achieve a desired detection probability with a significantly lower number of mobile nodes especially when the detection requirements are highly stringent. Similarly, when the target is mobile the coverage-based mobility model produces a consistently higher detection probability compared to other models under investigation.Comment: 7 pages, 12 figures, appeared in INFOCOM 201

Approximation Algorithm for Line Segment Coverage for Wireless Sensor Network

The coverage problem in wireless sensor networks deals with the problem of covering a region or parts of it with sensors. In this paper, we address the problem of covering a set of line segments in sensor networks. A line segment ` is said to be covered if it intersects the sensing regions of at least one sensor distributed in that region. We show that the problem of finding the minimum number of sensors needed to cover each member in a given set of line segments in a rectangular area is NP-hard. Next, we propose a constant factor approximation algorithm for the problem of covering a set of axis-parallel line segments. We also show that a PTAS exists for this problem.Comment: 16 pages, 5 figures

MINIMAX FILTERING IN WIRELESS SENSOR AND ACTOR NETWORKS

In this paper to handle the mobility of actors a hybrid strategy that includes location updating and location prediction is used.The usage of Kalman Filtering in location prediction high power and energy consumptions. To avoid the drawbacks of Kalman Filtering in location prediction, we make use of Minimax filtering (also Known as H∞ filtering). Minimax Filter has been used in WSANs by minimizing the estimation error and maximizing the worst case adversary noise. Minimax filtering will also minimize power and energy consumptions

Using Multi-agent System for Solving Coverage Problem in Wireless Sensor Network

Wireless sensor network (WSN) is one of the most important paradigms in computer networks because of the widespread applications. Coverage problem is a fundamental issue in sensor networks that reflects how the network is controlled by the sensors, this problem appears when any node becomes failure or out of the range, in this case the area will be disconnected and the data will not send to the destination. We present a new approach which uses a multi-agent system to solve this problem and perform an easy and secure network. In order to do that we implement sensor network by four phases: first construct a virtual network by matlab, second we use k-means clustering to cluster nodes in k-groups, third put the intelligent sensor in each cluster to be as a head for its group, fourth we divide the network to four regions and the closet agent to the sink will be the delegate to send the aggregated data from its region to the destination. Therefore, we tried to minimize the power consumption in WSN, we save the energy by keeping it sleep until it has a task to do , at this case the node changes its status to be in active mode and when it finishes it will be idle

Estimation and Improvements of the Fundamental QoS in Networks with Random Topologies

The computer communication paradigm is moving towards the ubiquitous computing and Internet of Things (IoT). Small autonomous wirelessly networked devices are becoming more and more present in monitoring and automation of every human interaction with the environment, as well as in collecting various other information from the physical world. Applications, such as remote health monitoring, intelligent homes, early fire, volcano, and earthquake detection, traffic congestion prevention etc., are already present and all share the similar networking philosophy. An additional challenging for the scientific and engineering world is the appropriateness of the alike networks which are to be deployed in the inaccessible regions. These scenarios are typical in environmental and habitat monitoring and in military surveillance. Due to the environmental conditions, these networks can often only be deployed in some quasi-random way. This makes the application design challenging in the sense of coverage, connectivity, network lifetime and data dissemination. For the densely deployed networks, the random geometric graphs are often used to model the networking topology. This paper surveys some of the most important approaches and possibilities in modeling and improvement of coverage and connectivity in randomly deployed networks, with an accent on using the mobility in improving the network functionality

Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network

Node placement is one of the fundamental issues that affects the performance of coverage and connectivity in Wireless Sensor Network (WSN). In a large scale WSN, sensor nodes are deployed randomly where they are scattered too close or far apart from each other. This random deployment causes issues such as coverage hole, overlapping and connectivity failure that contributes to the performance of coverage and connectivity of WSN. Therefore, node placement model is develop to find the optimal node placement in order to maintain the coverage and guaranteed the connectivity in random deployment. The performance of Extended Virtual Force-Based Algorithm (EVFA) and Cuckoo Search (CS) algorithm are evaluated and EVFA shows the improvement of coverage area and exhibits a guaranteed connectivity compared to CS algorithm. Both algorithms have their own strength in improving the coverage performance. The EVFA approach can relocate the sensor nodes using a repulsive and attractive force after initial deployment and CS algorithm is more efficient in exploring the search of maximum coverage area in random deployment. This study proposed Extended Virtual Force and Cuckoo Search (EVFCS) algorithm with a combination of EVFA and CS algorithm to find an optimal node placement. A series of experimental studies on evaluation of proposed algorithm were conducted within simulated environment. In EVFCS, the algorithm searches the best value of threshold distance and relocated the new position of sensor nodes. The result suggested 18.212m is the best threshold distance that maximizes the coverage area. It also minimizes the problems of coverage hole and overlapping while guaranteeing a reasonable connectivity quality. It proved that the proposed EVFCS outperforms the EVFA approach and achieved a significant improvement in coverage area and guaranteed connectivity. The implementation of the EVFCS improved the problems of initial random deployment

Estimation and Improvements of the Fundamental QoS in Networks with Random Topologies

The computer communication paradigm is moving towards the ubiquitous computing and Internet of Things (IoT). Small autonomous wirelessly networked devices are becoming more and more present in monitoring and automation of every human interaction with the environment, as well as in collecting various other information from the physical world. Applications, such as remote health monitoring, intelligent homes, early fire, volcano, and earthquake detection, traffic congestion prevention etc., are already present and all share the similar networking philosophy. An additional challenging for the scientific and engineering world is the appropriateness of the alike networks which are to be deployed in the inaccessible regions. These scenarios are typical in environmental and habitat monitoring and in military surveillance. Due to the environmental conditions, these networks can often only be deployed in some quasi-random way. This makes the application design challenging in the sense of coverage, connectivity, network lifetime and data dissemination. For the densely deployed networks, the random geometric graphs are often used to model the networking topology. This paper surveys some of the most important approaches and possibilities in modeling and improvement of co verage and connectivity in randomly deployed networks, with an accent on using the mobility in improving the network functionality