Titlebook: Web Proxy Cache Replacement Strategies; Simulation, Implemen Hala ElAarag Book 2013 Hala ElAarag 2013 Cache Replacement.NNPCR.Neural Networ

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Neural Networks,ts (neurons) which when combined are able to approximate functions based on data sets. Neural networks typically mimic biologic neurons by using a set of weights, one for each connection, which is similar to the exciting and inhibiting properties of actual neurons. By adjusting these weights such th

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A Quantitative Study of Web Cache Replacement Strategies Using Simulation, decreasing network traffic, reducing user perceived lag and loads on origin servers. Despite that some Web 2.0 applications have dynamic objects, most of the Web traffic has static content with file types such as cascading style sheets, javascript files, images, etc. The cache replacement strategie

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Web Proxy Cache Replacement Scheme Based on Backpropagation Neural Network,s chapter, a novel approach to web proxy cache replacement is developed and analyzed. Unlike previous approaches, this approach utilizes neural networks for replacement decisions. The neural networks are trained to classify cacheable objects from real-world data sets using information known to be im

Density

Web Proxy Cache Replacement Scheme Based on Backpropagation Neural Network,s chapter, a novel approach to web proxy cache replacement is developed and analyzed. Unlike previous approaches, this approach utilizes neural networks for replacement decisions. The neural networks are trained to classify cacheable objects from real-world data sets using information known to be im

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Implementation of a Neural Network Proxy Cache Replacement Strategy in the Squid Proxy Server, to end users in an appropriate time frame. Web caching was introduced in the 1990s to help decrease network traffic, lessen user perceived lag, and reduce loads on origin servers by storing copies of web objects on servers closer to end users as opposed to forwarding all requests to the origin serv

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