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Adaptive access-point and channel selection method using Markov approximation

Author

Listed:
  • Tomotaka Kimura
  • Kouji Hirata
  • Masahiro Muraguchi

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.

Suggested Citation

  • Tomotaka Kimura & Kouji Hirata & Masahiro Muraguchi, 2018. "Adaptive access-point and channel selection method using Markov approximation," International Journal of Distributed Sensor Networks, , vol. 14(2), pages 15501477187, February.
    • Handle: RePEc:sae:intdis:v:14:y:2018:i:2:p:1550147718761584
    DOI: 10.1177/1550147718761584
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    References listed on IDEAS

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    1. Andrew Whitmore & Anurag Agarwal & Li Xu, 2015. "The Internet of Things—A survey of topics and trends," Information Systems Frontiers, Springer, vol. 17(2), pages 261-274, April.
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