Stackelberg博弈的MEC资源分配策略

移动边缘计算(mobile edge computing，MEC)通过在网络边缘部署计算资源成为缓解终端设备资源匮乏的有效方案。针对设备计算资源无法满足任务需求的问题，提出一种基于Stackelberg博弈的MEC资源分配策略。该策略应用Stackelberg博弈理论将请求方、协作方的卸载过程描述为效用最大化问题以激发双方的协作积极性，并设计一种基于粒子群的Stackelberg博弈算法，以快速获得该优化问题的最优解。同时，由于区块链具有分布式、不可篡改等特性，出于对安全性的考虑，将其应用于协作过程的管理。实验结果表明，所提策略可以实现双方联合效用最大化，且相较于遗传算法的卸载方案;所提算法具有更快的收敛性能。

MEC resource allocation strategy under the Stackelberg game

Mobile edge computing (MEC) has become an effective solution to alleviate the scarcity of end devices by deploying computing resources at the edge of the network. To address the problem that the computing resources of the device cannot meet the task demand, this paper proposed an MEC resource allocation strategy based on the Stackelberg game. The strategy uses the Stackelberg game theory to describe the offloading process of the requesting and collaborating parties as a utility maximization problem to motivate both parties to collaborate, and designs a particle swarm-based Stackelberg game algorithm that aims to quickly obtain an optimal solution to this optimization problem. At the same time, due to the distributed and tamper-proof nature of the blockchain, it is applied to the management of the collaboration process for security reasons. Experimental results verify that the proposed strategy can maximize the joint utility of both parties, and compared to the offloading scheme of the genetic algorithm, the proposed algorithm has faster convergence performance.