Heuristics for lifetime maximization in camera sensor networks

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• 作者：Alok Singh ; ^a ; ^{alokcs@uohyd.ernet.in} ; André ; Rossi^b ; ^{andre.rossi@univ-angers.fr} ; Marc Sevaux^c ; ^{marc.sevaux@univ-ubs.fr}
• 关键词：Camera sensor network ; Genetic algorithm ; Heuristic ; Network lifetime maximization problem
• 刊名：Information Sciences
• 出版年：2017
• 出版时间：April 2017
• 年：2017
• 卷：385-386
• 期：Complete
• 页码：475-491
• 全文大小：570 K
• 卷排序：385

文摘

Due to increasing threat perception and cheap availability of multimedia technologies, camera sensor networks are becoming more and more popular these days. Camera sensor networks pose some unique challenges in addition to the usual difficulties associated with any directional sensor network. This paper addresses the problem of maximizing the network lifetime in camera sensor networks under the full and the partial target coverage models. In the full target coverage model, all the targets are assumed to be covered during the entire lifetime, whereas in the partial target coverage model, targets are supposed to have weights according to their importance, and only a fraction of targets with sum of weights above a certain threshold need to be covered during the entire lifetime. Three heuristics are presented for this problem. The first heuristic is an improved version of an already existing heuristic. Other two heuristics are based on column generation and utilize a linear programming solver to solve the master problem, whereas a genetic algorithm is used to solve the NPNP-hard subproblem. Computational results show the effectiveness of our proposed heuristics.