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http://dx.doi.org/10.3745/KTCCS.2021.10.11.291

Energy-Efficient MEC Offloading Decision Algorithm in Industrial IoT Environments  

Koo, Seolwon (숙명여자대학교 IT공학과)
Lim, YuJin (숙명여자대학교 IT공학과)
Publication Information
KIPS Transactions on Computer and Communication Systems / v.10, no.11, 2021 , pp. 291-296 More about this Journal
Abstract
The development of the Internet of Things(IoT) requires large computational resources for tasks from numerous devices. Mobile Edge Computing(MEC) has attracted a lot of attention in the IoT environment because it provides computational resources geographically close to the devices. Task offloading to MEC servers is efficient for devices with limited battery life and computational capability. In this paper, we assumed an industrial IoT environment requiring high reliability. The complexity of optimization problem in industrial IoT environment with many devices and multiple MEC servers is very high. To solve this problem, the problem is divided into two. After selecting the MEC server considering the queue status of the MEC server, we propose an offloading decision algorithm that optimizes reliability and energy consumption using genetic algorithm. Through experiments, we analyze the performance of the proposed algorithm in terms of energy consumption and reliability.
Keywords
Mobile Edge Computing; Offloading; Genetic Algorithm; Industrial Internet of Things;
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