Abstract-Multimedia cloud, as a specific cloud paradigm, addresses how cloud can effectively process multimedia services and provide QoS provisioning for multimedia applications. There are two major challenges in multimedia cloud. The first challenge is the service response time in multimedia cloud, and the second challenge is the cost of cloud resources. In this paper, we optimize resource allocation for multimedia cloud based on queuing model. Specifically, we optimize the resource allocation in both singleclass service case and multiple-class service case. In each case, we formulate and solve the response time minimization problem and resource cost minimization problem, respectively. Simulation results demonstrate that the proposed optimal allocation scheme can optimally utilize the cloud resources to achieve a minimal mean response time or a minimal resource cost.

With the emergence of cloud computing, cloudbased multimedia applications have been increasingly adopted in recent years. There are two major challenges for multimedia application providers: the round trip time (RTT) requirement and the resource cost. In this paper, we study the virtual machine (VM) allocation problem for multimedia application providers to minimize the resource cost under RTT requirements. Specifically, we propose the optimal VM allocation schemes for single-site cloud and multi-site cloud, respectively. Moreover, we propose the greedy algorithms to efficiently allocate VMs in each case. Simulation results demonstrate that the proposed optimal VM allocation schemes can optimally allocate VMs to achieve a minimal resource cost.

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Cloud-based multimedia services have been widely used in recent years. As the growing scale, users often have quite diverse quality of service (QoS) expectations. A key challenge for differentiated services is how to optimally allocate cloud resources to satisfy different users. In this paper, we study resource allocation problems for differentiated multimedia services. We first propose a queueing model to characterize differentiated services in cloud. Based on the model, we optimize cloud resources in the first-come first-served (FCFS) scenario and priority scenario. In each scenario, we formulate and solve the optimal resource allocation problem to minimize resource cost under response time constraints. We conduct extensive simulations with practical parameters of Amazon EC2. Simulation results demonstrate that the proposed resource allocation schemes can optimally configure resources to provide satisfactory services at the minimal resource cost.