A Color-Based Cooperative Caching Strategy for Time-Shifted Live Video Streaming

Abstract

This paper proposes an efficient in-network caching strategy to reduce traffic volume for pseudo-live video streaming networks. Pseudo-live streaming is a technique that records video data as fragmented files in a cache server and reproduces them by continuously combining the fragments. The recorded video data can be treated as static video files. Therefore, in-network caching techniques could efficiently reduce network traffic by carefully managing cache servers and important contents arrangement. The proposed in-network caching strategy tries to cache popular chunking video fragments with taking account of the freshness of the data in a cooperative way among distributed cache servers. We extend a color-based cooperative cache algorithm, which is recently proposed for contents delivery networks, to effectively treat time-shifting video chunks. The extension strategy determines an optimal cache placement before starting content delivery based on the generation of the data and its multiple video quality structures of the real-time streaming. In our experiment, traffic volume is calculated from access probability and the number of hops of communication, and a content arrangement is selected in such a way that the total communication distance in the network becomes the smallest. We conduct a network simulation with traffic patterns that are generated from content access probability of gamma distribution for a three-layer hierarchical structure network. Simulation results show that the traffic volume is reduced up to 50% and 40% compared with conventional LRU and LFU methods, respectively.