Multiuser computation offloading for edge-cloud collaboration using submodular optimization

被引：0

作者：

Liang B. ^{[1
,2
,3
]}

Ji W. ^{[1
,3
,4
]}

机构：

[1] Institute of Computing Technology, Chinese Academy of Sciences, Beijing

[2] School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing

[3] Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing

[4] Peng Cheng Laboratory, Shenzhen

来源：

Tongxin Xuebao/Journal on Communications | 2020年 / 41卷 / 10期

基金：

中国国家自然科学基金; 国家重点研发计划;

关键词：

Cloud computing; Edge computing; Edge-cloud computing; Multiuser computation offloading; Submodular optimization;

D O I：

10.11959/j.issn.1000-436x.2020205

中图分类号：

学科分类号：

摘要：

A computation offloading scheme based on edge-cloud computing was proposed to improve the system utility of multiuser computation offloading. This scheme improved the system utility while considering the optimization of edge-cloud resources. In order to tackle the problems of computation offloading mode selection and edge-cloud resource allocation, a greedy algorithm based on submodular theory was developed by fully exploiting the computing and communication resources of cloud and edge. The simulation results demonstrate that the proposed scheme effectively reduces the delay and energy consumption of computing tasks. Additionally, when computing tasks are offloaded to edge and cloud from devices, the proposed scheme still maintains stable system utilities under ultra-limited resources. © 2020, Editorial Board of Journal on Communications. All right reserved.

引用

页码：25 / 36

页数：11

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