Publication Type
Journal Article
Version
submittedVersion
Publication Date
4-2015
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.
Keywords
Wireless sensor networks, Markov decision processes (MDPs), stochastic control, optimization methods, decision-making tools, multi-agent systems
Discipline
Computer Sciences | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
IEEE Communications Surveys and Tutorials
Volume
17
Issue
3
First Page
1239
Last Page
1267
ISSN
1553-877X
Identifier
10.1109/COMST.2015.2420686
Publisher
IEEE
Citation
ALSHEIKH, Abu Mohammad; HOANG, Dinh Thai; NIYATO, Dusit; and Hwee-Pink TAN.
Markov decision processes with applications in wireless sensor networks: A survey. (2015). IEEE Communications Surveys and Tutorials. 17, (3), 1239-1267.
Available at: https://ink.library.smu.edu.sg/sis_research/2855
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/COMST.2015.2420686