 Adaptive access-point and channel selection method using Markov approximationTomotaka Kimura, Kouji Hirata and Masahiro Muraguchi International Journal of Distributed Sensor Networks, 2018, vol. 14, issue 2, 1550147718761584 Abstract: This article proposes an access-point and channel selection method for Internet of Things environments. Recently, the number of wireless nodes has increased with the growth of Internet of Things technologies. In order to accommodate traffic generated by the wireless nodes, we need to utilize densely placed wireless access-points. This article introduces a joint optimization problem of access-point and channel selection for such an environment. The proposed method deals with the optimization problem, using Markov approximation which adapts to dynamic changes in network conditions. Markov approximation is a distributed optimization framework, where a network is optimized by individual behavior of users forming a time-reversible continuous-time Markov chain. The proposed method searches optimal solution for the access-point and channel selection problem on the time-reversible continuous-time Markov chain. Simulation experiments demonstrate the effectiveness of the proposed method. Keywords: Internet of Things; access-point selection; channel selection; Markov approximation; optimization problem (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:14:y:2018:i:2:p:1550147718761584 Access Statistics for this article More articles in International Journal of Distributed Sensor Networks |
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