One Size Doesn't Fit All: Improving Network QoS Through Preference-driven Web Caching

Abstract

In order to combat Internet congestion Web caches use replacement policies that attempt to keep the objects in a cache that are most likely to get requested in the future. We adopt the economic perspective that the objects with the greatest value to the users should be in a cache. Using trace driven simulations we implement an incentive compatible market-based Web cache for servers to push content into a cache. This system decentralizes the caching process as servers provide information in the form of bids for space in the cache. Truthful information from the server on valuations of objects and predictions of hit rates is obtained. This information is used in filling the cache, which can provide increased aggregate value and differential quality of service to servers when compared to LFU and LRU.