Sweep-coverage with energy-restricted mobile wireless sensor nodes

  • Authors:
  • Meng Yang;Donghyun Kim;Deying Li;Wenping Chen;Hongwei Du;Alade O. Tokuta

  • Affiliations:
  • School of Information, Renmin University of China, Beijing, China;Department of Mathematics and Computer Science, North Carolina Central University, Durham, NC;School of Information, Renmin University of China, Beijing, China;School of Information, Renmin University of China, Beijing, China;Department of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China,Shenzhen Key Laboratory of Internet Information Collaboration, Shenzhen, Chi ...;Department of Mathematics and Computer Science, North Carolina Central University, Durham, NC

  • Venue:
  • WASA'13 Proceedings of the 8th international conference on Wireless Algorithms, Systems, and Applications
  • Year:
  • 2013

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Abstract

Most of the existing results in sweep-coverage focused on minimizing the number of the mobile sensor nodes by carefully planning their corresponding trajectories such that each target of interest can be periodically monitored (within every t time unit). However, the starting locations of the mobile sensors, at which the service depots (or equivalently base stations) of the nodes are usually located, are never considered in the trajectory planning. In order to provide sweep-coverage for a long period of time, each node also needs to periodically visit a base station to replace a battery or refueled (within every T time unit). Motivated by this observation, this paper introduces two new sweep-coverage problems, in which each mobile sensor node is required to visit a base station periodically, namely (t,T)-SCOPe-1 and (t,T)-SCOPe-M, each of which considers one single base station and M base stations for all of the nodes, respectively. We prove those problems are NP-hard and propose heuristic algorithms for them. In addition, we conduct simulations to evaluate the average performance of the proposed algorithms and study their average behavior characteristics.