Open Access

ARTICLE

Edge Cloud Selection in Mobile Edge Computing (MEC)-Aided Applications for Industrial Internet of Things (IIoT) Services

Dae-Young Kim¹, SoYeon Lee², MinSeung Kim², Seokhoon Kim^1,*

1 Department of Computer Software Engineering, Soonchunhyang University, Asan, 31538, Korea
2 Department of Software Convergence, Soonchunhyang University, Asan, 31538, Korea

* Corresponding Author: Seokhoon Kim. Email:

Computer Systems Science and Engineering 2023, 47(2), 2049-2060. https://doi.org/10.32604/csse.2023.040473

Received 20 March 2023; Accepted 15 May 2023; Issue published 28 July 2023

Abstract

In many IIoT architectures, various devices connect to the edge cloud via gateway systems. For data processing, numerous data are delivered to the edge cloud. Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency. There are two types of costs for this kind of IoT network: a communication cost and a computing cost. For service efficiency, the communication cost of data transmission should be minimized, and the computing cost in the edge cloud should be also minimized. Therefore, in this paper, the communication cost for data transmission is defined as the delay factor, and the computing cost in the edge cloud is defined as the waiting time of the computing intensity. The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs. That is, a device chooses a routing path to the selected edge cloud based on the costs. The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load. The performance of the proposed method is validated through extensive computer simulation. When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states, the proposed method reduced both the average delay and the service pause counts to about 25% of the existing method.

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Keywords

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