Journal
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
Volume 17, Issue 3, Pages 1239-1267Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/COMST.2015.2420686
Keywords
Wireless sensor networks; Markov decision processes (MDPs); stochastic control; optimization methods; decision-making tools; multi-agent systems
Funding
- Singapore MOE Tier 1 [RG18/13, RG33/12]
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Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are used to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs.
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