Long Term Channel Allocation Strategies for Video Applications

Abstract

In typical video delivery systems offering programs on-demand, service should be nearly immediate and continuous. A video server can provide this type of service by reserving sufficient network and server resources for the duration of playout. Scalability and reduced cost can be achieved using a single channel to serve multiple customers waiting for the same program (referred to as batching). Batching is especially useful during high load periods typically occuring during evening prime time hours. Typical channel allocation algorithms use a greedy, allocate-as-needed policy. Variations in system load can cause these algorithms to suffer poor and unpredictable short-term performance, and non-optimal long term performance. In this paper, we develop a set of realistic workloads, identify the limitations of greedy allocation algorithms, and propose a set of rate-based allocation schemes to solve these limitations. The performance of various video delivery systems are simulated and compared. The rate-based policies are shown to be robust for the workloads examined, and are easy to implement.