Title
Adaptive Access-Point And Channel Selection Method Using Markov Approximation
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.
Year
DOI
Venue
2018
10.1177/1550147718761584
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
Keywords
Field
DocType
Internet of Things, access-point selection, channel selection, Markov approximation, optimization problem
Computer science,Markov chain,Internet of Things,Communication channel,Optimization problem,Distributed computing
Journal
Volume
Issue
ISSN
14
2
1550-1477
Citations 
PageRank 
References 
0
0.34
9
Authors
3
Name
Order
Citations
PageRank
Tomotaka Kimura1118.82
Kouji Hirata21011.28
masahiro muraguchi393.40