ScholarWorks@숙명여자대학교

초록

The development of the Internet of Things(IoT) requires large computational resources for tasks from numerous devices. Mobile EdgeComputing(MEC) has attracted a lot of attention in the IoT environment because it provides computational resources geographically closeto 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 environmentwith many devices and multiple MEC servers is very high. To solve this problem, the problem is divided into two. After selecting theMEC server considering the queue status of the MEC server, we propose an offloading decision algorithm that optimizes reliability andenergy consumption using genetic algorithm. Through experiments, we analyze the performance of the proposed algorithm in terms ofenergy consumption and reliability.

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