A Reliable Energy Efficient Algorithm for Target Coverage in Wireless Sensor Networks

• Published in: 2010 IEEE 30th International Conference on Distributed Computing Systems Workshops pp. 180 - 188
• Main Authors: Jing He, Naixue Xiong, Yang Xiao, Yi Pan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2010
• Subjects: Energy Efficiency; Equations; Mathematical model; Maximum Reliability Sensor Covers; Monitoring; Probability; Reliability; Sensor Scheduling; Sensors; Target Coverage; Wireless sensor networks
• DOI: 10.1109/ICDCSW.2010.53
• ISBN: 9781424474714; 142447471X
• ISSN: 1545-0678

A critical aspect of applications in Wireless Sensor Networks (WSNs) is network lifetime. Power-constrained WSNs are usable as long as they can communicate sensed data to a processing node. Poor communication links and hazard environment make the WSNs unreliable. The existing schemes only consider that the state of a sensor covering targets is in binary mode: success (cover the targets) or fail (cannot cover the targets). However in the real WSNs, a sensor covers targets with a certain probability. To improve WSNs' reliability, we should consider the fact that a sensor covers targets with users'satisfied probability. To solve the above problem, this paper first introduces failure probability into target coverage problems to improve and control the system's reliability. Furthermore, we model the solution as the Maximum Reliability Sensor Covers (MRSC)problem and design a heuristic greedy algorithm that efficiently compute the maximal number of reliable sensor covers. To efficiently extend the WSNs' lifetime with users' pre-defined failure probability requirements, only the sensors from the current active sensor cover is responsible for monitoring all targets, while all other sensors are in a low-energy sleep mode. Finally, simulation results validate the performance of our proposed algorithm, in which users can precisely control the system's reliability without sacrificing the energy consumption too much.