Towards dynamic resource optimization for cloud-based free viewpoint video service

Recent years have witnessed the fast development of cloud-based media services. For service providers (SP), a key challenge is how to provide satisfactory services at a low cost. In this paper, we study the resource optimization for cloud-based free viewpoint video (FVV) service. We propose a Two-time-scale Resource Configuration (TRC) model. Specifically, cloud resources are allocated in a mid-long time scale and dynamically reconfigured in a fine-grained time scale. Based on the model, we formulate and solve the resource cost minimization problem and the response time minimization problem, respectively. We have implemented a prototype of cloud-based FVV on a cluster of machines. Experimental results demonstrate that the proposed resource optimization schemes not only allocate resources effectively to achieve the low cost, but also reconfigure resources dynamically to obtain the low response time.