Computation Offloading in Multi-Cell Networks With Collaborative Edge-Cloud Computing: A Game Theoretic Approach

被引:10
|
作者
Wu, Liantao [1 ,2 ]
Sun, Peng [3 ]
Wang, Zhibo [4 ]
Li, Yanjun [5 ]
Yang, Yang [6 ,7 ,8 ]
机构
[1] Shanghai Tech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China
[2] East China Normal Univ, Software Engn Inst, Shanghai 200062, Peoples R China
[3] Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Peoples R China
[4] Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310027, Peoples R China
[5] Zhejiang Univ Technol, Sch Comp Sci & Technol, Hangzhou 310023, Peoples R China
[6] Terminus Grp, Beijing 100027, Peoples R China
[7] Peng Cheng Lab, Shenzhen 518055, Peoples R China
[8] Shenzhen Smart City Technol Dev Grp Co Ltd, Shenzhen 518046, Peoples R China
基金
中国国家自然科学基金;
关键词
Servers; Games; Task analysis; Costs; Delays; Cloud computing; Energy consumption; Collaborative edge-cloud computing; computation offloading; potential game; multi-cell interference; RESOURCE-ALLOCATION; OPTIMIZATION; MANAGEMENT;
D O I
10.1109/TMC.2023.3246462
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the widespread application of 5G and the Internet of things (IoT), edge computing and cloud computing have been collaboratively utilized for task offloading and processing. However, though the massive devices (e.g., smartphones) are organized into multi-cells, most of the existing works do not explore the computation offloading for edge-cloud computing under inter-cell interference. Thus, the offloading decisions may be inappropriate as the transmission rate is overestimated. To address this issue, we propose COMEC, a novel Computation Offloading scheme in Multi-cell networks with Edge-Cloud collaboration, which could minimize the total cost in terms of delay and energy consumption. Specifically, we first formulate COMEC as an optimization problem taking into account inter-cell interference. Then, considering the offloading decisions of all users are coupled, a non-cooperative game is formulated to minimize the total cost of each user in a distributed manner. We prove that this game is a general (ordinal) potential game and possesses a pure strategy Nash equilibrium (NE). Based on the finite improvement property of the potential game, we develop the corresponding computation offloading algorithm to achieve the NE. Finally, simulation results show that the proposed scheme can achieve superior performance in overall system cost compared with other baselines.
引用
收藏
页码:2093 / 2106
页数:14
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