Markov decision processes with applications in wireless sensor networks: A survey

Mohammad Abu Alsheikh, Dinh Thai Hoang, Dusit Niyato, Hwee Pink Tan, Shaowei Lin

Research output: Contribution to journalArticle

86 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number7080987
Pages (from-to)1239-1267
Number of pages29
JournalIEEE Communications Surveys and Tutorials
Volume17
Issue number3
DOIs
Publication statusPublished - 1 Jul 2015
Externally publishedYes

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