Stackelberg Differential Game Based Resource Sharing in Hierarchical Fog-Cloud Computing

Jun Du, Chunxiao Jiang, A. Benslimane, Song Guo, Yong Ren
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引用次数: 6

Abstract

The tremendous increase of computation-heavy applications has posed great challenges in terms of enhanced service coverage and high-speed data processing in the Fifth Generation (5G) networks. As responding, the integrated fog and cloud computing (FCC) system has been expected as an efficient approach to support low-latency and on-demand computing services. This work considers the computing resource market in an FCC system operated by one cloud computing service provider (CCP) and multiple fog computing service providers (FCPs), in which the CCP shares its cloud computing resource among FCPs and itself to serve users with computational tasks. To facilitate the resource trading between the CCP and FCPs, a Stackelberg differential game based resource sharing mechanism is proposed. In this mechanism, performance discrepancy is introduced as a penalty factor to denote the mismatch between the resource supply and demand, which will encourage all computing providers (CPs) to make their trading decisions that can truthfully reflect their resource capacity and requirements. In addition, an evolutionary game based replicator dynamics is established to analyze the users' service selection among CPs. Based on the established hierarchical game framework, interactions between user selection and computing resource sharing are investigated. The performance of the designed resource sharing mechanism is validated in the simulations, which also reveal the convergence and equilibrium states of user selection, resource pricing and resource allocation.
基于Stackelberg差分对策的分层雾云计算资源共享
计算密集型应用的大量增加对第五代(5G)网络的增强业务覆盖和高速数据处理提出了巨大挑战。作为响应,集成雾和云计算(FCC)系统被期望作为支持低延迟和按需计算服务的有效方法。本研究考虑了由一个云计算服务提供商(CCP)和多个雾计算服务提供商(fcp)运营的FCC系统中的计算资源市场,其中CCP在fcp和自己之间共享其云计算资源,为用户提供计算任务。为了促进CCP和fcp之间的资源交易,提出了一种基于Stackelberg差分博弈的资源共享机制。在该机制中,引入性能差异作为惩罚因素来表示资源供需之间的不匹配,这将鼓励所有计算提供商(CPs)做出能够真实反映其资源容量和需求的交易决策。在此基础上,建立了基于进化博弈的复制因子动力学模型,分析了用户的服务选择。在建立的分层博弈框架的基础上,研究了用户选择与计算资源共享之间的交互关系。仿真结果验证了所设计的资源共享机制的性能,揭示了用户选择、资源定价和资源分配的收敛和均衡状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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