Adaptive access-point and channel selection method using Markov approximation

Tomotaka Kimura,Masahiro Muraguchi,Kouji Hirata

doi:10.1177/1550147718761584

Tomotaka Kimura, Masahiro Muraguchi + Show 1 more

Open Access

https://doi.org/10.1177/1550147718761584

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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.

Highlights

A huge number of network devices have connected to the Internet, which leads to the realization of Internet of Things (IoT).[1,2,3,4,5]
We propose a new accesspoint and channel selection method using Markov approximation in order to adapt to dynamic changes in network conditions
We have proposed a new method for selecting accesspoints and channels using Markov approximation

Summary

Introduction

A huge number of network devices have connected to the Internet, which leads to the realization of Internet of Things (IoT).[1,2,3,4,5] The number of network devices will further increase with the growth of IoT technologies. Zhu et al.[15] have proposed a channel selection method for sensor networks in IoT environments, which utilizes the multi-armed bandit model This method assumes dynamic situations, but does not consider an access-point selection problem. We deal with a joint optimization problem of access-point and channel selection for IoT environments, considering dynamic situations. The proposed method searches approximate solution for the joint optimization problem of access-point and channel selection on the time-reversible continuous-time Markov chain, aiming at maximizing the minimum throughput of wireless nodes. Under situations where users dynamically arrive and depart, we need to obtain the optimal strategy zÃ 2 Z(t) in order to maximize the utility every time the system conditions change. Before we explain the proposed access-point and channel selection method, we introduce the following MIP that maximizes the minimum throughput of users at a given time t.

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Conclusion