Distributed multimedia proxy cache replacement algorithms
Abstract
Implementation of caches in multimedia proxy servers can significantly improve the delivery of media by reducing media retrieval latency, reducing network bandwidth usage, increasing the number of clients that can be served simultaneously, and increasing the fault tolerance of the server system. An important component of proxy server caches is the cache object replacement algorithm, which determines which objects are removed from the cache when storage space is needed for placing new objects into the cache. These algorithms must effectively predict which currently cached objects are not expected to be accessed in the near future so they can be removed. However, these algorithms must also be fast; i.e. they cannot be too computationally complex, because these algorithms must execute often on caches that usually contain a large number of objects. Current implementations of proxy cache servers (Squid, Inktomi Traffic Server, Novell Internet Caching System, etc.) use the least-recently used cache replacement algorithm, but a number of other object statistics could be used as part of the cache replacement algorithm calculations. This research presents the fully-associative, variable block size cache replacement algorithm problem as a unique model which illuminates a new method for looking at cache replacement algorithm issues. The study then explores the use of a variety of cache object statistics and how well these other statistics help predict the expected future demand for cached objects. Simulations are used as the method of comparison, and actual and stochastic data from WWW traces, commercial hotel video system traces, and educational multimedia system video traces are used as simulation input. Also, the effectiveness of admission policies and caching large videos is explored. Not only will the findings from this study impact the World-Wide Web caching infrastructure and distributed multimedia system implementations, but the findings can also influence the efficiency of distributed databases and other distributed information systems.
Degree
Ph.D.
Advisors
Meyer, Purdue University.
Subject Area
Electrical engineering|Computer science
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