Non-orthogonal multiple access-based MEC for energy-efficient task offloading in e-commerce systems

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发表在:Journal of Cloud Computing vol. 13, no. 1 (Dec 2024), p. 117
主要作者: Zheng, Xiao
其他作者: Tahir, Muhammad, Aurangzeb, Khursheed, Anwar, Muhammad Shahid, Aamir, Muhammad, Farzan, Ahmad, Ullah, Rizwan
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Springer Nature B.V.
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100 1 |a Zheng, Xiao  |u Shandong University of Technology, School of Computer Science and Technology, Zibo, P.R. China (GRID:grid.412509.b) (ISNI:0000 0004 1808 3414); Qilu University of Technology (Shandong Academy of Sciences), Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Jinan, China (GRID:grid.443420.5) (ISNI:0000 0000 9755 8940) 
245 1 |a Non-orthogonal multiple access-based MEC for energy-efficient task offloading in e-commerce systems 
260 |b Springer Nature B.V.  |c Dec 2024 
513 |a Journal Article 
520 3 |a Mobile edge computing (MEC) reduces the latency for end users to access applications deployed at the edge by offloading tasks to the edge. With the popularity of e-commerce and the expansion of business scale, server load continues to increase, and energy efficiency issues gradually become more prominent. Computation offloading has received widespread attention as a technology that effectively reduces server load. However, how to improve energy efficiency while ensuring computing requirements is an important challenge facing computation offloading. To solve this problem, using non-orthogonal multiple access (NOMA) to increase the efficiency of multi-access wireless transmission, MEC supporting NOMA is investigated in the research. Computing resources will be divided into separate sub-computing that will be handled via e-commerce terminals or transferred to edge sides by reutilizing radio resources, we put forward a Group Switching Matching Algorithm Based on Resource Unit Allocation (GSM-RUA) algorithm that is multi-dimensional. To this end, we first formulate this task allocation problem as a long-term stochastic optimization problem, which we then convert to three short-term deterministic sub-programming problems using Lyapunov optimization, namely, radio resource allocation in a large timescale, computation resource allocating and splitting in a small-time frame. Of the 3 short-term deterministic sub-programming problems, the first sub-programming problem can be remodeled into a 1 to n matching problem, which can be solved using the block-shift-matching-based radio resource allocation method. The latter two sub-programming problems are then transformed into two continuous convex problems by relaxation and then solved easily. We then use simulations to prove that our GSM-RUA algorithm is superior to the state-of-the-art resource management algorithms in terms of energy consumption, efficiency and complexity for e-commerce scenarios. 
653 |a Matching 
653 |a Servers 
653 |a End users 
653 |a Optimization 
653 |a Edge computing 
653 |a Resource allocation 
653 |a Mobile computing 
653 |a Programming 
653 |a Computation offloading 
653 |a Algorithms 
653 |a Energy efficiency 
653 |a Electronic commerce 
653 |a Resource management 
653 |a Energy consumption 
653 |a Nonorthogonal multiple access 
700 1 |a Tahir, Muhammad  |u Mohammad Ali Jinnah University, Department of Computer Science, Karachi, Pakistan (GRID:grid.444794.e) (ISNI:0000 0004 1755 056X) 
700 1 |a Aurangzeb, Khursheed  |u King Saud University, Department of Computer Engineering, College of Computer and Information Sciences, Riyadh, Saudi Arabia (GRID:grid.56302.32) (ISNI:0000 0004 1773 5396) 
700 1 |a Anwar, Muhammad Shahid  |u Gachon University, Department of AI and Software, Seongnam-si, South Korea (GRID:grid.256155.0) (ISNI:0000 0004 0647 2973) 
700 1 |a Aamir, Muhammad  |u Huanggang Normal University, College of Computer Science, Huanggang, China (GRID:grid.443405.2) (ISNI:0000 0001 1893 9268) 
700 1 |a Farzan, Ahmad  |u Youwe Digital Agency, Kerry Hill, Horsforth, Leeds, UK (GRID:grid.443405.2) 
700 1 |a Ullah, Rizwan  |u Chulalongkorn University, Department of Electrical Engineering, Bangkok, Thailand (GRID:grid.7922.e) (ISNI:0000 0001 0244 7875) 
773 0 |t Journal of Cloud Computing  |g vol. 13, no. 1 (Dec 2024), p. 117 
786 0 |d ProQuest  |t Research Library 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3071634517/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
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