Aggregate Profit-Based Caching Replacement Algorithms for Streaming Media Transcoding Proxy Systems

This work derives a generalized video object profit function from the extended weighted transcoding graph to calculate the individual cache profit of certain versions of a video object, and the aggregate profit from caching multiple versions of the same video object. This proposed function takes into account the popularity of certain versions of an object, the transcoding delay among versions, and the average duration of access of each version. Based on the profit function, cache-replacement algorithms are proposed to reduce the startup delay and network traffic by efficiently caching video objects with the most profits. Two kinds of simulations were conducted to evaluate the performance of the proposed algorithms. These simulations exploit partial viewing traces and complete viewing traces, separately. The results demonstrate that the proposed algorithms outperform the competing algorithms by 15%-39% in delay saving ratio and 5%-10% in byte-hit ratio