Performance and Precision of Web Caching Simulations Including a Random Generator for Zipf Request Pattern
The steadily growing Internet traffic volume for video, IP-TV and other content needs support by caching systems and architectures which are provided in global content delivery networks as well as in local networks, on home gateways or user terminals. The efficiency of caching is important in order to save transport capacity and to improve throughput and delays.
However, since analytic solutions for the hit rate as the main caching performance measure are not available even under the baseline scenario of an independent request model (IRM) with usual Zipf request pattern and caching strategies, simulation methods are used to evaluate caching efficiency. Based on promising experience with simulation approaches of caching methods in previous work, we study and verify two main prerequisites: First, a fast random Zipf rank generator is derived, which allows to extend simulations to billions of requests. Moreover, the accuracy of alternatives of the hit rate evaluation is compared based on the 2nd order statistics. The results indicate that the sum of request probabilities of objects in the cache provides a more precise estimator of the hit rate as a simple hit count.
KeywordsSimulation of caching strategies Least Recently Used (LRU) Score gated LRU Least Frequently Used (LFU) Zipf request pattern Random zipf rank generator 2nd order statistics Hit rate estimators
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