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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.