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

Abu Alsheikh, M; Hoang, DT; Niyato, D; Tan, HP; Lin, S

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

Abu Alsheikh, M Hoang, DT Niyato, D Tan, HP Lin, S

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Communications Surveys and Tutorials, 2015, 17, (3), pp. 1239-1267
Issue Date:: 2015-07-01

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Field	Value	Language
dc.contributor.author	Abu Alsheikh, M
dc.contributor.author	Hoang, DT
dc.contributor.author	Niyato, D
dc.contributor.author	Tan, HP
dc.contributor.author	Lin, S
dc.date.accessioned	2023-03-21T05:29:17Z
dc.date.available	2023-03-21T05:29:17Z
dc.date.issued	2015-07-01
dc.identifier.citation	IEEE Communications Surveys and Tutorials, 2015, 17, (3), pp. 1239-1267
dc.identifier.issn	1553-877X
dc.identifier.issn	1553-877X
dc.identifier.uri	http://hdl.handle.net/10453/167963
dc.description.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.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Communications Surveys and Tutorials
dc.relation.isbasedon	10.1109/COMST.2015.2420686
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0805 Distributed Computing, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.title	Markov decision processes with applications in wireless sensor networks: A survey
dc.type	Journal Article
utslib.citation.volume	17
utslib.for	0805 Distributed Computing
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2023-03-21T05:29:14Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	17
utslib.citation.issue	3

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.

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http://hdl.handle.net/10453/167963