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首页> 外文会议>IEEE International Conference on Tools with Artificial Intelligence >Optimize Pricing Policy in Evolutionary Market with Multiple Proactive Competing Cloud Providers
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Optimize Pricing Policy in Evolutionary Market with Multiple Proactive Competing Cloud Providers

机译：通过多个主动竞争的云提供商优化演化市场中的定价策略

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摘要

In the cloud computing market with multiple competing cloud providers, each provider needs to run an optimize pricing policy to determine the price for cloud resources in order to beat other providers and maximize the long-term revenue. In this paper, we intend to design an optimal pricing policy for the cloud provider by taking into account the following two facts: (1) the market is evolutionary in terms of the increased amount of cloud users and the decreased marginal cost of providers; (2) the market is fully competitive since all providers expect to receive more profits while users expect to pay less for their requirements. By considering these realistic situations, we analyze how the cloud provider designs an optimal pricing policy while competing against the other provider. Specifically, we model the pricing issue in the competing environment as a Markov games, and then adopt the Minimax-Q and Q-learning algorithm to find the optimal pricing policy. Finally, we evaluate our algorithms and compare the pricing policy with other existing polices. Numerical simulations demonstrate the effectiveness of our proposed approach.
机译：在具有多个竞争云提供商的云计算市场中，每个提供商都需要运行优化定价策略来确定云资源的价格，以便击败其他提供商并最大化长期收入。在本文中，我们打算考虑以下两个事实为云提供商设计最佳定价策略：（1）从云用户数量的增加和提供商边际成本的降低来看，市场是演进的; （2）市场完全竞争，因为所有提供商都希望获得更多利润，而用户希望为自己的需求支付更少的费用。通过考虑这些现实情况，我们分析了云提供商在与其他提供商竞争时如何设计最佳定价策略。具体来说，我们将竞争环境中的定价问题建模为马尔可夫博弈，然后采用Minimax-Q和Q学习算法来找到最佳定价策略。最后，我们评估算法并将定价政策与其他现有政策进行比较。数值模拟证明了我们提出的方法的有效性。

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