Cloud-Edge-End Collaborative Intelligent Service Computation Offloading: A Digital Twin Driven Edge Coalition Approach for Industrial IoT

被引：0
作者：
Li, Xiaohuan [1 ,2 ]
Chen, Bitao [3 ]
Fan, Junchuan [3 ]
Kang, Jiawen [4 ]
Ye, Jin [5 ]
Wang, Xun [3 ]
Niyato, Dusit [6 ]
机构：
[1] Guilin Univ Elect Technol, Sch Informat & Commun, Key Lab Intelligent Networking & Scenario Syst, Guilin 541004, Peoples R China
[2] Natl Engn Lab Comprehens Transportat Big Data Appl, Guangxi Res Inst Integrated Transportat Big Data, Nanning 530001, Peoples R China
[3] Guilin Univ Elect Technol, Sch Informat & Commun, Guilin 541004, Peoples R China
[4] Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China
[5] Guangxi Univ, Sch Comp & Elect Informat, Nanning 530004, Peoples R China
[6] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore 639798, Singapore
来源：
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT | 2024年 / 21卷 / 06期
基金：
新加坡国家研究基金会; 中国国家自然科学基金;
关键词：
Cloud computing; Industrial Internet of Things; Task analysis; Optimization; Games; Computational modeling; Heuristic algorithms; Cloud-edge-end; digital twin (DT); coalition game; computation offloading; RESOURCE-ALLOCATION; MANAGEMENT; NETWORKS; GAME;
D O I：
10.1109/TNSM.2024.3441231
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
By using the intelligent edge computing technologies, a large number of computing tasks of end devices in Industrial Internet of Things (IIoT) can be offloaded to edge servers, which can effectively alleviate the burden and enhance the performance of IIoT. However, in large-scale multi-service-oriented IIoT scenarios, offloading service resources are heterogeneous and offloading requirements are mutually exclusive and time-varying, which reduce the offloading efficiency. In this paper, we propose a cloud-edge-end collaboration intelligent service computation offloading scheme based on Digital Twin (DT) driven Edge Coalition Formation (DECF) approach to improve the offloading efficiency and the total utility of edge servers, respectively. Firstly, we establish a DT model to obtain accurate digital representations of heterogeneous end devices and network state parameters in dynamic and complex IIoT scenarios. The DT model can capture time-varying requirements in a low latency manner. Secondly, we formulate two optimization problems to maximize the offloading throughput and total system utility. Finally, we convert the multi-objective optimization problems to a Stackelberg coalition game model and develop a distributed coalition formation approach to balance the two optimizing objectives. Simulation results indicate that, compared with the nearest coalition scheme and non-coalition scheme, the proposed approach achieves offloading throughput improvements of 11.5% and 148%, and enhances the overall utility by 12% and 170%, respectively.
引用
收藏
页码：6318 / 6330
页数：13
相关论文
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