Server scheduler design for distributed video-on-demand service

Abstract

Online media server scheduling algorithms in distributed video-on-demand (VoD) systems are studied in this work. We first identify the failure rate and the server-side network bandwidth consumption as two main cost factors in a distributed VoD service model. The proposed distributed server scheduler consists of two parts: the request migration scheme and the dynamic content update strategy. By improving the random early migration (REM) scheme, we propose a cost-aware REM (CAREM) scheme to reduce the network bandwidth consumption due to the migration process. Furthermore, to accommodate the change in video popularity and/or client population, we use the server-video affinity to measure the potential server-side bandwidth cost after placing a specific video copy on that server. The dynamic content update strategy uses the server-video affinity to reconfigure video copies on media servers. We conduct extensive simulations to evaluate the performance of the proposed algorithm. It can be shown that CAREM together with the dynamic content update strategy can improve the system performance by reducing the request failure rate as well as the server bandwidth consumption.