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A Stackelberg game approach to multiple resources allocation and pricing in mobile edge computing

机译:移动边缘计算中多种资源分配和定价的Stackelberg游戏方法

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摘要

Mobile edge computing is a new paradigm that can enhance the computation capability of end devices and alleviate communication traffic loads during transmission. Mobile edge computing is highly useful for emerging resource-hungry mobile applications. However, a key challenge for mobile edge computing systems is multiple resources allocation between Mobile Edge Clouds (MECs) and End Users (EUs), especially for multiple heterogeneous MECs and EUs. To address this problem, we propose a Stackelberg game-based framework in which EUs and MECs act as followers and leaders, respectively. The proposed framework aims to compute a Stackelberg equilibrium solution in which each MEC achieves the maximum revenue while each EU obtains utility-maximized resources under budget constraints. We decompose the multiple resources allocation and pricing problem into a set of subproblems in which each subproblem only considers a single resource type. The Stackelberg game framework is constructed for each subproblem wherein each player (i.e., an EU) can selfishly maximize its utility by selecting an appropriate strategy in the strategy space. We prove the existence of the subgame Stackelberg equilibrium and develop algorithms to determine the Stackelberg equilibrium for each resource type, including an optimal demand computation algorithm, to determine the best resource demand strategy for an EU and an iterative algorithm to find an equilibrium price. The equilibrium solutions of all subgames constitute the equilibrium solution of the original problem. We also conduct simulation experiments of our game, such as numerical data for the Stackelberg equilibrium, numerical data for the convergence of the Stackelberg equilibrium, and numerical data as the system size increases. Finally, we demonstrate that an EU with idle resources can play the role of an MEC.
机译:移动边缘计算是一种新的范例,可以增强终端设备的计算能力并减轻传输过程中的通信流量负载。移动边缘计算对于需要大量资源的移动应用程序非常有用。但是,移动边缘计算系统面临的主要挑战是在移动边缘云(MEC)和最终用户(EU)之间分配多种资源,尤其是对于多个异构MEC和EU。为了解决这个问题,我们提出了一个基于Stackelberg游戏的框架,在该框架中,欧盟和中东和非洲分别充当追随者和领导者。拟议的框架旨在计算Stackelberg均衡解决方案,其中每个MEC都获得最大收益,而每个EU在预算约束下获得效用最大化的资源。我们将多种资源分配和定价问题分解为一组子问题,其中每个子问题仅考虑一种资源类型。 Stackelberg游戏框架是为每个子问题构建的,其中每个玩家(即欧盟)可以通过在策略空间中选择适当的策略来自私地最大化其效用。我们证明了子游戏Stackelberg均衡的存在,并开发了确定每种资源类型的Stackelberg均衡的算法,包括最优需求计算算法,确定欧盟的最佳资源需求策略和迭代算法以找到均衡价格。所有子博弈的均衡解构成了原始问题的均衡解。我们还进行了游戏的模拟实验,例如用于Stackelberg平衡的数值数据,用于Stackelberg平衡收敛的数值数据,以及随着系统规模增加而产生的数值数据。最后,我们证明拥有闲置资源的欧盟可以扮演MEC的角色。

著录项

  • 来源
    《Future generation computer systems》 |2020年第7期|273-287|共15页
  • 作者单位

    College of Computer Science and Electronic Engineering Hunan University Changsha 410082 China Key Laboratory for Embedded and Network Computing of Hunan Province Changsha 410082 China;

    College of Information and Management Hunan University of Finance and Economics Changsha 410205 China;

    Department of Computer Science State University of New York New Paltz NY 12561 United States of America;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Game theory; Mobile edge computing; Multiple resources allocation; Resource pricing;

    机译:博弈论;移动边缘计算;多种资源分配;资源定价;

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