On the scalability of an image transcoding proxy server

Image transcoding proxies are used to improve Web browsing over low bandwidth networks by adapting content-rich Web images to bandwidth-constrained clients. Such transcoding proxies dynamically analyze, manipulate and transcode images (e.g. quality reduction, down sampling) on the fly enabling significant reductions in download times over low bandwidth links. However, transcoding proxies have scalability problems if the objective policy that decides whether to transcode an image does not take the client load (e.g. number of concurrent clients) into consideration. We show that seemingly intuitive policies that make decisions solely based on whether transcoding yields savings in transmission time tail to scale. Under high load, the average latency perceived by a client can be improved by a factor of about two by taking overall client load into consideration and properly scheduling transcoding operations on a single CPU. We show that an earliest deadline first (EDF) based scheduling policy further improves transcoding performance.