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Cost Optimization of Elasticity Cloud Resource Subscription Policy

机译:弹性云资源订阅策略的成本优化

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In cloud computing, resource subscription is an important procedure which enables customers to elastically subscribe to IT resources based on their service requirements. Resource subscription can be divided into two categories, namely long-term reservation and on-demand subscription. Although customers need to pay the upfront fee for a long-term reservation contract, the usage charge of reserved resources is generally much cheaper than that of the on-demand subscription. To provide a better Internet service by using cloud resource, service operators will expect to make a trade-off between the amount of long-term reserved resources and that of on-demand subscribed resources. Therefore, how to properly make resource provision plans is a challenging issue. In this paper, we present a two-phase algorithm for service operators to minimize their service provision cost. In the first phase, we propose a mathematical formulae to compute the optimal amount of long-term reserved resources. In the second phase, we use the Kalman filter to predict resource demand and adaptively change the subscribed on-demand resources such that provision cost could be minimized. We evaluated our solution by using real-world data. Our numerical results indicated that the proposed mechanisms are able to significantly reduce the provision cost.
机译:在云计算中,资源订阅是一个重要过程,可让客户根据其服务需求灵活地订阅IT资源。资源订阅可以分为两类,即长期预订和按需订阅。尽管客户需要为长期预订合同支付前期费用,但是预留资源的使用费用通常比按需订阅便宜。为了通过使用云资源提供更好的Internet服务,服务运营商将期望在长期保留的资源量和按需订阅的资源量之间进行权衡。因此,如何正确制定资源供应计划是一个具有挑战性的问题。在本文中,我们为服务运营商提出了一种两阶段算法,以最大程度地减少其服务提供成本。在第一阶段,我们提出一个数学公式来计算长期保留资源的最佳数量。在第二阶段,我们使用卡尔曼滤波器来预测资源需求并自适应地更改已订阅的按需资源,从而可以最大程度地降低供应成本。我们通过使用实际数据评估了我们的解决方案。我们的数值结果表明,所提出的机制能够显着降低提供成本。

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