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Fairness-oriented computation offloading for cloud-assisted edge computing
DOI:10.1016/j.future.2021.10.004.png)
摘要
En 中文
Mobile edge computing, which enhances the computing power of mobile devices via computation offloading technology, has been proposed as a promising paradigm to alleviate the mismatch between limited computational resources and ever-increasing computational requirements. An appropriate offloading strategy must be identified to optimize the computation offloading performance. Moreover, a mobile user is generally a selfish individual; therefore, we should consider the fairness problem when determining the offloading strategy. In this paper, we focus on computation offloading in a cloud-assisted edge computing system with multiple users, an edge server and a cloud server and aim to optimize the response time for each user. A fairness-oriented approach, including the determination of the application offloading strategy, the data transmission strategy and the cloud-edge cooperation strategy, is proposed. Initially, the computation offloading problem is formulated as a noncooperative game. Then, we find the optimal cloud-edge cooperation strategy and the optimal data transmission strategy based on a theoretical analysis and propose an iterative algorithm to identify the optimal offloading strategy for each user. Finally, we evaluate the proposed approach by means of extensive experiments, and the experimental results show that the proposed approach can significantly reduce the response time of mobile devices. (c) 2021 Elsevier B.V. All rights reserved.
Keyword:
Cloud-assisted edge computing
Computation offloading
Fairness-oriented approach
期刊
F
IF:
6.1
论文数:
6.8K
被引数:
2.3W
机构
引用论文
FairEdge: A Fairness-Oriented Task Offloading Scheme for Iot Applications in Mobile Cloudlet Networks
IEEE ACCESS
IF3.6
Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks多服务器移动边缘计算网络的联合任务卸载和资源分配
Efficient resource assignment in mobile edge computing: A dynamic congestion-aware offloading approach移动边缘计算中的高效资源分配: 一种动态拥塞感知的卸载方法

