Periodic cache replacement policy for dynamic content at application server
Decision Support Systems
Analyzing Document-Duplication Effects on Policies for Browser and Proxy Caching
INFORMS Journal on Computing
A new approach for a proxy-level web caching mechanism
Decision Support Systems
Performance evaluation for implementations of a network of proxy caches
Decision Support Systems
An admission-control technique for delay reduction in proxy caching
Decision Support Systems
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Neuro-fuzzy system in partitioned client-side Web cache
Expert Systems with Applications: An International Journal
Cooperative Cashing? An Economic Analysis of Document Duplication in Cooperative Web Caching
Information Systems Research
SOA Performance Enhancement Through XML Fragment Caching
Information Systems Research
Estimating instantaneous cache hit ratio using Markov chain analysis
IEEE/ACM Transactions on Networking (TON)
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Experience shows that document caching by a web browser is a cheap and effective way to improve the performance of the World Wide Web. This study analyzes a LRU (Least Recently Used) policy for cache management in a web browser. In this policy, the cache is filled with documents based upon a document's "age," defined as the time elapsed since the document was last accessed. The user's preference for a document is modeled as a general function that declines with the document's age. Two popular measures--the expected delay per document access, and the hit-ratio--are used to evaluate the LRU policy. Unlike many previous studies that evaluate caching policies using simulation methods, this study derives analytical expressions to evaluate performance. The study also presents an approximate, easy-to-compute method to evaluate performance. Numerical tests show this approximation to be extremely accurate. A variety of other numerical results are presented that help describe the behavior ofthe LRU policy under different situations (e.g., when the documents need to be updated periodically). We also compare the LRU policy with other caching policies (both static and dynamic) for small problems. Our comparison suggests that finding a good caching policy that is conscious of document size and delay may be difficult.