Power-aware resource provisioning in cluster computing

The high power consumption of cluster computing infrastructures has become a major concern. It leads to the increased heat dissipation and decreased reliability of cluster servers. Power management becomes a critical issue in cluster computing. In this paper, we start with an analysis of the relationship between cluster performance and power consumption. We study both the problem of minimizing the average end-to-end delay with the constraint of average energy consumption and the problem of minimizing the average energy consumption of cluster service requests with the constraint of an average end-to-end delay for customer services. We propose novel approaches to solving these two problems. In an effort to maximize profits, a service provider only provides sufficient resources to ensure quality of services (QoS) but often avoid over provisioning to meet QoS defined in a service level agreement (SLA) which is a contract agreed between a customer and a service provider. We present an approach for optimizing SLA-based resource provisioning in cluster computing in that we minimize the total cost of cluster servers owned by a service provider while satisfying the requirements of both a percentile of the end-to-end delay and average energy consumption. Numerical experiments show that the proposed approach is efficient and accurate for the SLA-based resource provisioning problem in cluster computing.

集群计算基础设施的高能耗已成为一个主要问题。它导致集群服务器散热增加以及可靠性降低。电源管理成为集群计算中的一个关键问题。在本文中，我们首先分析集群性能和能耗之间的关系。我们研究了在平均能耗约束下最小化平均端到端延迟的问题，以及在客户服务的平均端到端延迟约束下最小化集群服务请求平均能耗的问题。我们提出了解决这两个问题的新方法。为了实现利润最大化，服务提供商仅提供足够的资源以确保服务质量（QoS），但通常避免过度配置以满足服务水平协议（SLA）中定义的QoS，SLA是客户和服务提供商之间达成的合同。我们提出了一种在集群计算中优化基于SLA的资源配置的方法，即我们在满足端到端延迟的百分位数和平均能耗的要求的同时，最小化服务提供商所拥有的集群服务器的总成本。数值实验表明，所提出的方法对于集群计算中基于SLA的资源配置问题是高效且准确的。