Optimal Connected Coverage For Wireless Sensor Networks
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Optimal Coverage in Wireless Sensor Networks
This book will serve as a reference, presenting state-of-the-art research on theoretical aspects of optimal sensor coverage problems. Readers will find it a useful tool for furthering developments on theory and applications of optimal coverage; much of the content can serve as material for advanced topics courses at the graduate level. The book is well versed with the hottest research topics such as Lifetime of Coverage, Weighted Sensor Cover, k-Coverage, Heterogeneous Sensors, Barrier, Sweep and Partial Coverage, Mobile Sensors, Camera Sensors and Energy-Harvesting Sensors, and more. Topics are introduced in a natural order from simple covers to connected covers, to the lifetime problem. Later, the book begins revisiting earlier problems ranging from the introduction of weights to coverage by k sensors and partial coverage, and from sensor heterogeneity to novel problems such as the barrier coverage problem. The book ends with coverage of mobile sensors, camera sensors, energy-harvesting sensors, underwater sensors, and crowdsensing.
Glowworm Swarm Optimization
This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intelligence and working on these topics.
Optimal Connected Coverage for Wireless Sensor Networks
Abstract: Coverage and connectivity are two key properties of wireless networks, particularly wireless sensor networks (WSNs). Deploying sensor nodes to simultaneously achieve coverage and connectivity requirements is a fundamental problem in WSNs. It is insufficient to consider coverage alone when deploying a wireless sensor network; connectivity must also be considered. While moderate loss of coverage can be tolerated by WSN applications, loss of connectivity can be fatal. Moreover, since sensors are subject to unanticipated failures after deployment, it is not sufficient for a wireless sensor network to just be connected, it should be k-connected (for k> 1). In this dissertation, we propose optimal deployment patterns to achieve both full coverage and k-connectivity for k=1,2,3,4,5, and 6, respectively, and prove their optimality for all values of r_c/r_s, where r_c is the communication radius and r_s is the sensing radius. By optimal deployment patterns, we mean those patterns that can achieve desired coverage and connectivity requirements with the fewest sensor nodes. Our results' fundamentality and generality facilitate their practical applications in, e.g., wireless mesh networks and 802.15.4 networks. We discover an interesting emph{pattern mutation} phenomenon in pattern evolution as r_c/r_s continuously changes. This phenomenon has both theoretical and practical implications. We also study several practical issues in wireless sensor network deployment in this dissertation.