The Journal of Supercomputing

, Volume 71, Issue 3, pp 1067–1094 | Cite as

A novel sleep scheduling scheme in green wireless sensor networks

Article

Abstract

Reduction of unnecessary energy consumption is becoming a major concern in green wireless sensor networks. Sleep scheduling is one of the efficient strategies to achieve energy saving. In this paper, we propose a novel scheme for the sleep scheduling, which is based on Decentralized Partially Observable Markov Decision Process (Dec-POMDP). A sleep scheduling algorithm with online planning (Dec-POP-SSA) with respect to Dec-POMDP is also presented. In Dec-POMDP, due to the hardness of obtaining the state spaces and the reward with mold-free environment, quasi-Monte Carlo is applied to collect state spaces such that the real-time acquisition of beliefs state is achieved, and the reward is evaluated in tracking reward and coverage connectivity intensity. Instead of producing the entire plan, Dec-POP-SSA need only find actions for the current step. We also give the theoretical analysis on the upper bound for Dec-POP-SSA. The numerical experiments show that Dec-POP-SSA may receive the highest reward.

Keywords

Wireless sensor networks Sleep scheduling Dec-POMDP  Quasi-Monte Carlo Upper bound 

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.School of Mathematics and Computer ScienceFujian Normal UniversityFuzhouChina
  2. 2.School of Information Science and EngineeringFujian University of TechnologyFuzhouChina
  3. 3.Fujian Provincial Key Laboratory of Network Security and Cryptology, Fujian Normal UniversityFuzhouChina
  4. 4.Department of Computer ScienceUniversity of TsukubaTsukuba Science CityJapan

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