Non-orthogonal multiple access-based MEC for energy-efficient task offloading in e-commerce systemsopen access
- Authors
- Zheng, Xiao; Tahir, Muhammad; Aurangzeb, Khursheed; Anwar, Muhammad Shahid; Aamir, Muhammad; Farzan, Ahmad; Ullah, Rizwan
- Issue Date
- Jun-2024
- Publisher
- SPRINGER
- Keywords
- Mobile edge computing (MEC); E-commerce; MEC offloading; Energy optimization; Non-orthogonal multiple access (NOMA); Resource allocation
- Citation
- JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, v.13, no.1
- Journal Title
- JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
- Volume
- 13
- Number
- 1
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/92144
- DOI
- 10.1186/s13677-024-00680-2
- ISSN
- 2192-113X
2192-113X
- Abstract
- 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.
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