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Multi-leader Multi-follower Stackelberg Game Based Dynamic Resource Allocation for Mobile Cloud Computing Environment

机译:基于多领导多追随者Stackelberg游戏的移动云计算环境动态资源分配

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摘要

Emerging mobile cloud computing (MCC) technology offers great potential for the mobile terminals to support running highly sophisticated applications. However, supporting such applications needs efficient resource management from cloud servers and mobile terminals. Moreover, the resource management technologies based on quality of experiences (QoE) can meet the demand of end users in a better way than those based on quality of services. In this paper, we address the resource management problem of MCC network with an acceptable QoE. Based on multi-leader multi-follower two-stage Stackelberg game model, the proposed scheme maximizes the utility function of MCC networks. Considering the scenario in which the cloud servers and mobile terminals are selfish to maximize their own interests, the network performance is greatly affected by their greediness. To achieve better network performance, control decisions are coupled with one another. Utility function considers not only the spectral efficiency and user satisfaction in the mobile terminal but also the pricing information in the cloud. Our proposed scheme can obtain a well-balanced performance between mobile terminals and cloud servers. In addition, the existence of Nash equilibrium in the proposed scheme is investigated. Theoretically, the maximum and minimum selling prices of bandwidth are deduced. Simulation results show that the effectiveness of the proposed algorithm and our proposed scheme outperforms equal allocation scheme in terms of the user satisfaction and network revenue.
机译:新兴移动云计算(MCC)技术为移动终端提供了很大的潜力,支持运行高度复杂的应用程序。但是,支持这些应用程序需要从云服务器和移动终端的有效资源管理。此外,基于经验质量(QoE)的资源管理技术可以以比基于服务质量更好的方式满足最终用户的需求。在本文中,我们通过可接受的QoE解决了MCC网络的资源管理问题。基于多领导多跟随器两级Stackelberg游戏模型,该方案最大限度地提高了MCC网络的实用功能。考虑到云服务器和移动终端是自私的场景,以最大化自己的兴趣,网络性能受到他们的贪婪的影响。为了实现更好的网络性能,控制决策彼此耦合。实用程序不仅考虑了移动终端中的光谱效率和用户满意度,还考虑了云中的定价信息。我们所提出的计划可以在移动终端和云服务器之间获得良好的平衡性能。此外,研究了在所提出的方案中存在纳什均衡。从理论上讲,推导出带宽的最高和最低销售价格。仿真结果表明,在用户满意度和网络收入方面,提出算法的有效性和我们提出的方案优于平等的分配方案。

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