Research Article
Task Offloading and Resource Allocation in an Unfair Environment in Mobile Edge Computing
@INPROCEEDINGS{10.1007/978-3-030-90196-7_47, author={Yiping Li and Yu Tang and Di Lin and Yuan Gao and Jiang Cao}, title={Task Offloading and Resource Allocation in an Unfair Environment in Mobile Edge Computing}, proceedings={Artificial Intelligence for Communications and Networks. Third EAI International Conference, AICON 2021, Xining, China, October 23--24, 2021, Proceedings, Part I}, proceedings_a={AICON}, year={2021}, month={11}, keywords={MEC Computing offloading Resource allocation}, doi={10.1007/978-3-030-90196-7_47} }- Yiping Li
Yu Tang
Di Lin
Yuan Gao
Jiang Cao
Year: 2021
Task Offloading and Resource Allocation in an Unfair Environment in Mobile Edge Computing
AICON
Springer
DOI: 10.1007/978-3-030-90196-7_47
Abstract
This paper studies the problem of offloading and resource allocation of user tasks when the user group’s tasks are divided into primary tasks and secondary tasks in Mobile Edge Computing (MEC) networks. In order to ensure that the computing of primary user tasks is not disturbed. This paper proposes a parameter called calculating interference ratio (CIR), and uses CIR to limit the resources allocated by the server to secondary user tasks. In addition, the problem of offloading and resource allocation is transformed into a mixed integer programming problem (MIP). Then, we use parallel DNN networks to generate offloading and caching decisions, and transform the MIP problem into a resource allocation problem. We verify the effectiveness of CIR in dealing with the resource allocation problem in such special scenarios through simulation.
