Modeling and Optimization of Meta-Caching Assisted Transcoding
The increase of aggregate Internet bandwidth and the rapid development of 3G wireless networks demand efficient delivery of multimedia objects to all types of wireless devices. To handle requests from wireless devices at runtime, the transcoding-enabled caching proxy has been proposed to save transcoded versions to reduce the intensive computing demanded by online transcoding. Constrained by available CPU and storage, existing transcoding-enabled caching schemes always selectively cache certain transcoded versions, expecting that many future requests can be served from the cache. But such schemes treat the transcoder as a black box, leaving no room for flexible control of joint resource management between CPU and storage. In this paper, we first introduce the idea of meta-caching by looking into a transcoding procedure. Instead of caching certain selected transcoded versions in full, meta-caching identifies intermediate transcoding steps from which certain intermediate results (called metadata) can be cached so that a fully transcoded version can be easily produced from the metadata with a small amount of CPU cycles. Achieving big saving in caching space with possibly small sacrifice on CPU load, the proposed meta-caching scheme provides a unique method to balance the utilization of CPU and storage resources at the proxy. We further construct a model to analyze the meta-caching scheme. Based on the analysis, we propose AMTrac, Adaptive Meta-caching for Transcoding, which adaptively applies meta-caching based on the client request patterns and available resources. Experimental results show that AMTrac can significantly improve the system throughput over existing approaches.
meta-caching transcoding adaptation cpu intensive computing