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http://dx.doi.org/10.3745/KTCCS.2022.11.5.139

Performance Comparison of Task Partitioning Methods in MEC System  

Moon, Sungwon (숙명여자대학교 IT공학과)
Lim, Yujin (숙명여자대학교 IT공학과)
Publication Information
KIPS Transactions on Computer and Communication Systems / v.11, no.5, 2022 , pp. 139-146 More about this Journal
Abstract
With the recent development of the Internet of Things (IoT) and the convergence of vehicles and IT technologies, high-performance applications such as autonomous driving are emerging, and multi-access edge computing (MEC) has attracted lots of attentions as next-generation technologies. In order to provide service to these computation-intensive tasks in low latency, many methods have been proposed to partition tasks so that they can be performed through cooperation of multiple MEC servers(MECSs). Conventional methods related to task partitioning have proposed methods for partitioning tasks on vehicles as mobile devices and offloading them to multiple MECSs, and methods for offloading them from vehicles to MECSs and then partitioning and migrating them to other MECSs. In this paper, the performance of task partitioning methods using offloading and migration is compared and analyzed in terms of service delay, blocking rate and energy consumption according to the method of selecting partitioning targets and the number of partitioning. As the number of partitioning increases, the performance of the service delay improves, but the performance of the blocking rate and energy consumption decreases.
Keywords
MEC; Task Partitioning; Task Offloading; Task Migration;
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