基于博弈论的联邦云中qos感知的虚拟资源定价服务

Tienan Zhang
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引用次数: 1

摘要

近年来,联邦云平台以分布式的方式为各类用户提供云服务已成为一种很有前途的范例。为了争夺云用户,对于每个云提供商来说,选择最适合其服务质量并对云用户保持吸引力的最佳价格是至关重要的。在本文中,我们首先将单个云提供商的定价策略制定为约束优化规划问题,以分析云用户和云提供商的行为。然后,我们提出了一个基于博弈的模型,该模型引入了一组虚拟资源代理来帮助供应商调整价格,以达到全局最优解。理论分析证明了所提出的博弈模型的有效性,并在真实的云平台上进行了大量的实验来评估其性能。实验结果表明,所提出的定价模型可以显著提高云提供商的资源收入,并在各种性能指标方面为用户任务提供理想的服务质量(QoS)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A QoS-aware virtual resource pricing service based on game theory in federated clouds
Recently, federated cloud platform has become a promising paradigm to provide cloud services for various kinds of users in a distributed manner. To compete for cloud users, it is critically important for each cloud provider to select an optimal price that best corresponds to their service qualities as well as remains attractive to cloud users. In this paper, we first formulate the pricing strategy of individual cloud provider as a constrained optimisation programming problem to analyse the behaviours of both cloud users and cloud providers. Then, we present game-based model which introduces a set of virtual resource agents to help providers adjusting their prices with aiming at achieving a global optimal solution. Theoretical analysis is present to prove the validity and effectiveness of the proposed game model, and extensive experiments are conducted in a real-world cloud platform to evaluate its performance. The experimental results show that the proposed pricing model can significantly improve the resource revenue for cloud providers and provide desirable quality-of-service (QoS) for user tasks in terms of various performance metrics.
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