The paper discusses a resource management method at the cloud tenant level. It concerns efficiently running a profitable service on resources leased from a cloud infrastructure provider. Particularly, the paper focuses on services that handle parallelizable client requests, e.g, such a request can be processed using a MPI or a MapReduce program. The objective is to manage resource use to just satisfy the performance requirements of clients and avoid the common over-provisioning or under-provisioning problem. The proposed resource management method makes initial resource leasing plan based on client request profile and performance targets in service level agreements (SLAs). It then dynamically adjusts resource allocation based on monitoring data. Our extensive experiments show that the method is able to provision and efficiently use resources to just satisfy the SLA targets.
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