A novel sleep scheduling scheme in green wireless sensor networks

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• 作者：Jing Zhang (1) (2)
  Li Xu (1) (3)
  Shuming Zhou (1)
  Xiucai Ye (4)
  
  1. School of Mathematics and Computer Science ; Fujian Normal University ; Fuzhou ; China
  2. School of Information Science and Engineering ; Fujian University of Technology ; Fuzhou ; China
  3. Fujian Provincial Key Laboratory of Network Security and Cryptology ; Fujian Normal University ; Fuzhou ; China
  4. Department of Computer Science ; University of Tsukuba ; Tsukuba Science City ; Ibaraki ; Japan
  
• 关键词：Wireless sensor networks ; Sleep scheduling ; Dec ; POMDP ; Quasi ; Monte Carlo ; Upper bound
• 刊名：The Journal of Supercomputing
• 出版年：2015
• 出版时间：March 2015
• 年：2015
• 卷：71
• 期：3
• 页码：1067-1094
• 全文大小：1,715 KB
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• 刊物类别：Computer Science
• 刊物主题：Programming Languages, Compilers and Interpreters
  Processor Architectures
  Computer Science, general
  
• 出版者：Springer Netherlands
• ISSN：1573-0484

文摘

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.