Open Access

ARTICLE

Success Rate Queue-Based Relocation Algorithm of Sensory Network to Overcome Non-Uniformly Distributed Obstacles

Sooyeon Park¹, Moonseong Kim², Woochan Lee^{1, *}

1 Department of Electrical Engineering, Incheon National University, Incheon, 22012, Korea.
2 Department of Liberal Arts, Seoul Theological University, Bucheon, 14754, Korea.

* Corresponding Author: Woochan Lee. Email: .

Computers, Materials & Continua 2020, 65(2), 1181-1201. https://doi.org/10.32604/cmc.2020.011245

Received 28 April 2020; Accepted 01 June 2020; Issue published 20 August 2020

Abstract

With the recent development of big data technology that collects and analyzes various data, the technology that continuously collects and analyzes the observed data is also drawing attention. Moreover, its importance is growing in data collection in areas where people cannot access. In general, it is not easy to properly deploy IoT wireless devices for data collection in these areas, and it is also inappropriate to use general wheelbased mobile devices for relocation. Recently, researches have been actively carried out on hopping moving models in place of wheel-based movement for the inaccessible regions. The majority of studies, however, so far have unrealistic assumptions that all IoT devices know the overall state of the network and the current state of each device. Moreover, various physical terrain environments, such as coarse gravel and sand, can change from time to time, and it is impossible for all devices to recognize these changes in real-time. In this paper, with the migration success rate of IoT hopping devices being relocated, the method of estimating the varying environment is proposed. This method can actively reflect the changing environment in real-time and is a realistic distributed environment-based relocation protocol on behalf of non-realistic, theory-based relocation protocols. Also, one of the significant contributions of this paper is to evaluate its performance using the OMNeT++ simulation tool for the first time in the world to reflect actual physical environmental conditions. Compared to previous studies, the proposed protocol was able to actively reflect the state of the surrounding environment, which resulted in improved migration success rates and higher energy efficiency.

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Citations