A Multilevel Optimization Framework for Computation Offloading in Mobile Edge Computing
Joint Authors
Shan, Nanliang
Li, Yu
Cui, Xiaolong
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-27
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Mobile edge computing is a new computing paradigm that can extend cloud computing capabilities to the edge network, supporting computation-intensive applications such as face recognition, natural language processing, and augmented reality.
Notably, computation offloading is a key technology of mobile edge computing to improve mobile devices’ performance and users’ experience by offloading local tasks to edge servers.
In this paper, the problem of computation offloading under multiuser, multiserver, and multichannel scenarios is researched, and a computation offloading framework is proposed that considering the quality of service (QoS) of users, server resources, and channel interference.
This framework consists of three levels.
(1) In the offloading decision stage, the offloading decision is made based on the beneficial degree of computation offloading, which is measured by the total cost of the local computing of mobile devices in comparison with the edge-side server.
(2) In the edge server selection stage, the candidate is comprehensively evaluated and selected by a multiobjective decision based on the Analytic Hierarchy Process based on Covariance (Cov-AHP) for computation offloading.
(3) In the channel selection stage, a multiuser and multichannel distributed computation offloading strategy based on the potential game is proposed by considering the influence of channel interference on the user’s overall overhead.
The corresponding multiuser and multichannel task scheduling algorithm is designed to maximize the overall benefit by finding the Nash equilibrium point of the potential game.
Amounts of experimental results show that the proposed framework can greatly increase the number of beneficial computation offloading users and effectively reduce the energy consumption and time delay.
American Psychological Association (APA)
Shan, Nanliang& Li, Yu& Cui, Xiaolong. 2020. A Multilevel Optimization Framework for Computation Offloading in Mobile Edge Computing. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1194969
Modern Language Association (MLA)
Shan, Nanliang…[et al.]. A Multilevel Optimization Framework for Computation Offloading in Mobile Edge Computing. Mathematical Problems in Engineering No. 2020 (2020), pp.1-17.
https://search.emarefa.net/detail/BIM-1194969
American Medical Association (AMA)
Shan, Nanliang& Li, Yu& Cui, Xiaolong. A Multilevel Optimization Framework for Computation Offloading in Mobile Edge Computing. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1194969
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194969