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Title: On caching effectiveness of web clusters under persistent connections
Authors: Tang, Xueyan
Chanson, Samuel T.
Keywords: Caching performance
Web clusters
Persistent connections
Content-based algorithm
Content-blind algorithm
Request-grained level
Allocation dependency
Session-grained level
Session-affinity aware algorithm
Issue Date: Oct-2003
Citation: Journal of Parallel and Distributed Computing, v. 63, no. 10, Oct. 2003, p. 981-995.
Abstract: Due to the emergence of the HTTP/1.1 standards, persistent connections are increasingly being used in web retrieval. This paper studies the caching performance of web clusters under persistent connections, focusing on the difference between session-grained and request-grained allocation strategies adopted by the web switch. It is shown that the content-based algorithm considerably improves caching performance over the content-blind algorithm at the request-grained level. However, most of the performance gain is offset by the allocation dependency that arises when the content-based algorithm is used at the session-grained level. The performance loss increases with cluster size and connection holding time. An optimization problem is formulated to investigate the best achievable caching performance under session-grained allocation. Based on a heuristic approach, a session-affinity aware algorithm is presented that makes use of the correlation between the requests in a session. Experimental results show that while the session-affinity aware algorithm outperforms the content-based algorithm under session-grained allocation, this optimization cannot fully compensate for the performance loss caused by allocation dependency.
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