数据中心网络环境中交互问题的博弈论建模

Jun Gong, J. Liao, Zilu Kang
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引用次数: 0

摘要

云服务已被云服务提供商(csp)广泛部署在大型数据中心,为用户提供更好的性能和可靠性。但是,数据中心的选择可能会与isp运营的许多物理网络的多个流量工程(TE)发生交互,从而导致性能损失。本文提出了一种基于纳什议价解(NBS)的CSP和isp的合作方法,该方法考虑了帕累托最优性和公平性,以提高CSP和isp的绩效。然后,为了便于实际部署,我们还设计了一个分解算法来计算NBS。在不同的网络环境下进行了仿真以验证我们的分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Game Theoretic Modeling of Interaction Problems in Datacenter Network Environments
Cloud services have been widely deployed on Iarge-scale datacenters by Cloud Service Providers (CSPs) to provide users with better performance and reliability. However, interactions between datacenter selection and multiple traffic engineering (TE) of many physical networks operated by Internet Service Providers (ISPs) may occur, which may lead to performance loss. In this paper, we propose a cooperative approach based on Nash’s bargaining solution (NBS) for CSP and ISPs to improve their performance, which considers both Pareto optimality and fairness. Then, in order to facilitate the actual deployment, we also design a decomposition algorithm to calculate the NBS. Simulations are performed to verify our analysis on different network environments.
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