Heuristics for lifetime maximization in camera sensor networks

Alok Singh 1 André Rossi 2 Marc Sevaux 3
3 Lab-STICC_UBS_CID_DECIDE
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (UMR 3192), Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : 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 NP-hard subproblem. Computational results show the effectiveness of our proposed heuristics.
Type de document :
Article dans une revue
Information Sciences, Elsevier, 2017, 385-386, pp.475-491. 〈10.1016/j.ins.2017.01.017〉
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https://hal.archives-ouvertes.fr/hal-01435942
Contributeur : Marc Sevaux <>
Soumis le : lundi 16 janvier 2017 - 08:21:27
Dernière modification le : mercredi 21 février 2018 - 15:48:03

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Alok Singh, André Rossi, Marc Sevaux. Heuristics for lifetime maximization in camera sensor networks. Information Sciences, Elsevier, 2017, 385-386, pp.475-491. 〈10.1016/j.ins.2017.01.017〉. 〈hal-01435942〉

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