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A Game-Theoretical Approach for Resource Allocation in Mobile Edge Computing

机译:移动边缘计算资源分配的游戏理论方法

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In mobile edge computing (MEC), the computation resource of edge server is limited. Since the resource could be shared by multiple mobile users, it should be carefully allocated and efficiently utilized. In this paper, we adopt a price-based two-tier Stackelberg game to model an MEC system comprised by a single MEC server and multiple users, for which the computation resource is efficiently allocated. In this model, the MEC server acts as the leader who sets the price of its computation resource, and aims to maximize its revenue through renting this resource. The users play as followers who aim to minimize the weighted summation of the monetary cost and the energy consumption, where the weight is chosen by each user independently based on its monetary budget and the battery capacity. By adopting the iterative optimization, we propose a price-based resource optimization algorithm to achieve the Nash Equilibrium among users and the Stackelberg Equilibrium between the server and the users. Simulation results demonstrate that the proposed algorithm can improve the revenue of the server, and meantime reduce the monetary and energy cost for users.
机译:在移动边缘计算(MEC)中,边缘服务器的计算资源有限。由于资源可以由多个移动用户共享,因此应该仔细分配和有效地使用它。在本文中,我们采用基于价格的二层Stackelberg游戏来模拟由单个MEC服务器和多个用户组成的MEC系统,其中有效地分配计算资源。在此模型中,MEC服务器充当设置其计算资源价格的领导者,并旨在通过租用此资源来最大限度地提高其收入。用户扮演追随者,他们旨在最大限度地减少货币成本和能源消耗的加权总和,其中每个用户根据其货币预算和电池容量独立地选择权重。通过采用迭代优化,我们提出了一种基于价格的资源优化算法,实现了用户和用户之间的用户和Stackelberg均衡的纳什均衡。仿真结果表明,所提出的算法可以提高服务器的收入,同时减少用户的货币和能源成本。

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