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Joint Offloading and Resource Allocation With Diverse Battery Level Consideration in MEC System
Yunzhi Zhao1; Fen Hou2; Bin Lin3,4; Yuxuan Sun5
2023-01-06
Source PublicationIEEE Transactions on Green Communications and Networking
ISSN2473-2400
Volume7Issue:2Pages:609-625
Abstract

Most of existing works related to mobile edge computing (MEC) focused on the total energy consumption or task completion time. However, for the applications with multiple players as a whole, the diverse battery levels of players should be considered to achieve better quality of experience (QoE), which is reflected in the metrics of task completion time and the lifespan of service. In this paper, we focus on QoE and diversity of devices. By jointly considering the individual battery level of different devices, we formulate an optimization problem to minimize the task completion time of the system. Firstly, we propose two necessary conditions to achieve the optimal solution of the formulated problem. In addition, we transform the formulated problem into another problem, which can be used to judge whether a given value is feasible for the formulated problem based on the proposed optimal conditions and bisection searching (BSS) algorithm. Then, we propose a method named sub-channel (SC) matching based on virtual computation resource (SMVCR) to solve the transformed problem with low computational complexity. Simulation results indicate that the BSS-SMVCR algorithm has a good performance in task completion time compared with some existing algorithms, and also can significantly extend the lifespan of the corresponding service, which is reflected in the supporting number of offloading tasks.

KeywordBisection Searching Mobile Edge Computing Quality Of Experience Sub-channel Matching
DOI10.1109/TGCN.2022.3232700
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaTelecommunications
WOS SubjectTelecommunications
WOS IDWOS:001009931100005
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141
Scopus ID2-s2.0-85147209134
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Corresponding AuthorFen Hou
Affiliation1.University of Macau, State Key Laboratory of Internet of Things for Smart City, Department of Electrical and Computer Engineering, Macau, Macao
2.Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities, University of Macau, State Key Laboratory of IoT for Smart City, Department of Electrical and Computer Engineering, Macau, Macao
3.Dalian Maritime University, School of Information Science and Technology, Dalian, 116026, China
4.Peng Cheng Laboratory, Network Communication Research Centre, Shenzhen, 518052, China
5.Beijing Jiaotong University, School of Electronic and Information Engineering, Beijing, 100044, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Yunzhi Zhao,Fen Hou,Bin Lin,et al. Joint Offloading and Resource Allocation With Diverse Battery Level Consideration in MEC System[J]. IEEE Transactions on Green Communications and Networking, 2023, 7(2), 609-625.
APA Yunzhi Zhao., Fen Hou., Bin Lin., & Yuxuan Sun (2023). Joint Offloading and Resource Allocation With Diverse Battery Level Consideration in MEC System. IEEE Transactions on Green Communications and Networking, 7(2), 609-625.
MLA Yunzhi Zhao,et al."Joint Offloading and Resource Allocation With Diverse Battery Level Consideration in MEC System".IEEE Transactions on Green Communications and Networking 7.2(2023):609-625.
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