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Cloudlet Placement and Task Allocation in Mobile Edge Computing

TitleCloudlet Placement and Task Allocation in Mobile Edge Computing
Publication TypeJournal Article
Year of Publication2019
AuthorsYang, S., F. Li, M. Shen, X. Chen, X. Fu, and Y. Wang
JournalIEEE Internet of Things Journal
Volume6
Issue3
Start Page5853 - 5863
Date Published03/2019
Abstract

Mobile edge computing (MEC) offers a way to shorten the cloud servicing delay by building the small-scale cloud infrastructures, such as cloudlets at the network edge, which are in close proximity to end users. On one hand, it is energy consuming and costly to place each cloudlet on each access point (AP) to process the requested tasks. On the other hand, the service provider should provide delay-guaranteed service to end users, otherwise they may get revenue loss. In this paper, we first model how to calculate the task completion delay in MEC and mathematically analyze the energy consumption of different equipments in MEC. Subsequently, we study how to place cloudlets on the network and allocate each requested task to cloudlets and public cloud with the minimum total energy consumption without violating each task's delay requirement. We prove that this problem is NP-hard and propose a Benders decomposition-based algorithm to solve it. We also present a software-defined network (SDN)-based framework to deploy the proposed algorithm. Extensive simulations reveal that the proposed algorithm can achieve an (close-to-)optimal performance in terms of energy consumption and acceptance ratio compared with two benchmark heuristics.

DOI10.1109/JIOT.2019.2907605