Queueing model based resource optimization for multimedia cloud

• We optimize cloud resources considering both QoS requirement and resource cost.
• We propose queueing model to characterize service process in multimedia cloud.
• We study resource allocation problems in three different scenarios.
• We minimize the response time and minimize the resource cost in each scenario.

Multimedia cloud is a specific cloud computing paradigm, focusing on how cloud can effectively support multimedia services. For multimedia service providers (MSP), there are two fundamental concerns: the quality of service (QoS) and the resource cost. In this paper, we investigate these two fundamental concerns with queueing theory and optimization methods. We introduce a queueing model to characterize the service process in multimedia cloud. Based on the proposed queueing model, we study resource allocation problems in three different scenarios: single-service scenario, multi-service scenario, and priority-service scenario. In each scenario, we formulate and solve the response time minimization problem and the resource cost minimization problem, respectively. We conduct extensive simulations with practical parameters of Windows Azure. Simulation results demonstrate that the proposed resource allocation schemes can optimally allocate cloud resources for each service to achieve the minimal response time under a certain budget or guarantee the QoS provisioning at the minimal resource cost.