区块链支持的协作式边缘计算的联合任务分配和资源优化

Wenjing Xu, Wang Wei, Zuguang Li, Wu Qihui, Xianbin Wang
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引用次数: 0

摘要

协作边缘计算是处理 B5G 无线网络中计算密集型任务的一个有前途的方向。然而,来自不同运营商的边缘计算服务器(ECS)之间可能互不信任,因此无法保证合作的积极性。在本文中,我们提出了一个支持区块链的联盟协作边缘计算框架,用户可以将计算任务卸载给来自不同运营商的 ECS。为了最小化用户的总延迟,我们提出了一个联合任务卸载和资源优化问题,该问题受每个 ECS 计算能力的约束。我们应用 Tammer 分解法和启发式优化算法来获得最优解。最后,我们提出了一种基于声誉的节点选择方法,以促进共识进程,同时还考虑了基于完成时间的主节点选择,以避免某些边缘节点被垄断,增强区块链的安全性。仿真结果验证了所提算法的有效性,与非合作情况相比,总延迟最多可减少 40%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint task allocation and resource optimization for blockchain enabled collaborative edge computing
Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks. However, edge computing servers (ECSs) from different operators may not trust each other, and thus the incentives for collaboration cannot be guaranteed. In this paper, we propose a consortium blockchain enabled collaborative edge computing framework, where users can offload computing tasks to ECSs from different operators. To minimize the total delay of users, we formulate a joint task offloading and resource optimization problem, under the constraint of the computing capability of each ECS. We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution. Finally, we propose a reputation based node selection approach to facilitate the consensus process, and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain. Simulation results validate the effectiveness of the proposed algorithm, and the total delay can be reduced by up to 40% compared with the non-cooperative case.
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