Workload-Aware Resource Sharing and Cache Management for Scalable Video Streaming

Abstract

The required real-time and high-rate transfers for multimedia data severely limit the number of video streams that can be delivered concurrently. Resource-sharing techniques address this problem and can be classified into two main classes: stream merging and periodic broadcasting. We evaluate through extensive simulation major resource-sharing techniques from the two classes, considering different service models and video workloads. We utilize this extensive analysis in developing a workload-aware hybrid solution (WAHS) that combines the advantages of the best performers among resource-sharing techniques. Moreover, we propose a statistical cache management (SCM) approach and derive analytical models for optimal cache allocation to reduce further the demands on the disk I/O when various resource sharing techniques are used.