IaaS云中资源订阅策略的成本优化
Optimizing the Cost for Resource Subscription Policy in IaaS Cloud
摘要：
云计算允许用户高效、动态地配置计算资源以满足其IT需求。云提供商向客户提供两种订阅计划，即预订和按需。预订计划通常比按需计划便宜。如果预先知道实际的计算需求，则预留资源将是直接的。挑战在于如何进行适当的资源配置以及客户如何有效地购买预订和按需配置选项。为了解决这个问题，两个阶段的算法，提出了最小化服务提供成本在预订和按需计划。为了在资源预留过程中预留出正确的最优资源量，在第一阶段提出了一个数学公式。第二阶段采用卡尔曼滤波器进行资源需求预测。评估结果表明，两阶段算法可以显着降低供应成本，预测是合理的精度。
英文摘要：
Cloud computing allow the users to efficiently and dynamically provision computing resource to meet their IT needs. Cloud Provider offers two subscription plan to the customer namely reservation and on-demand. The reservation plan is typically cheaper than on-demand plan. If the actual computing demand is known in advance reserving the resource would be straightforward. The challenge is how to make properly resource provisioning and how the customers efficiently purchase the provisioning options under reservation and on-demand. To address this issue, two-phase algorithm are proposed to minimize service provision cost in both reservation and on-demand plan. To reserve the correct and optimal amount of resources during reservation, proposed a mathematical formulae in the first phase. To predict resource demand, use kalman filter in the second phase. The evaluation result shows that the two-phase algorithm can significantly reduce the provision cost and the prediction is of reasonable accuracy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
