Energy-Efficient MEC Offloading Decision Algorithm in Industrial IoT Environments


KIPS Transactions on Computer and Communication Systems, Vol. 10, No. 11, pp. 291-296, Nov. 2021
https://doi.org/10.3745/KTCCS.2021.10.11.291,   PDF Download:
Keywords: Mobile Edge Computing, offloading, genetic algorithm, Industrial Internet of Things
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.


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Cite this article
[IEEE Style]
S. Koo and Y. Lim, "Energy-Efficient MEC Offloading Decision Algorithm in Industrial IoT Environments," KIPS Transactions on Computer and Communication Systems, vol. 10, no. 11, pp. 291-296, 2021. DOI: https://doi.org/10.3745/KTCCS.2021.10.11.291.

[ACM Style]
Seolwon Koo and YuJin Lim. 2021. Energy-Efficient MEC Offloading Decision Algorithm in Industrial IoT Environments. KIPS Transactions on Computer and Communication Systems, 10, 11, (2021), 291-296. DOI: https://doi.org/10.3745/KTCCS.2021.10.11.291.