Adaptive and lazy segmentation based proxy caching for streaming media delivery

Abstract

Streaming media objects are often cached in segments. Previous segment-based caching strategies cache segments with constant or exponentially increasing lengths and typically favor caching the beginning segments of media objects. However, these strategies typically do not consider the fact that most accesses are targeted toward a few popular objects. In this paper, we argue that neither the use of a predefined segment length nor the favorable caching of the beginning segments is the best caching strategy for reducing network traffic. We propose an adaptive and lazy segmentation based caching mechanism by delaying the segmentation as late as possible and determining the segment length based on the client access behaviors in real time. In addition, the admission and eviction of segments are carried out adaptively based on an accurate utility function. The proposed method is evaluated by simulations using traces including one from actual enterprise server logs. Simulation results indicate that our proposed method achieves a 30% reduction in network traffic. The utility functions of the replacement policy are also evaluated with different variations to show its accuracy.