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Reseach Article

A Novel Web Optimization Technique using Enhanced Particle Swarm Optimization

Published on June 2015 by P.n.nesarajan, M.venkatachalam, T.ranganayaki
National Conference on Research Issues in Image Analysis and Mining Intelligence
Foundation of Computer Science USA
NCRIIAMI2015 - Number 1
June 2015
Authors: P.n.nesarajan, M.venkatachalam, T.ranganayaki
030cec94-c1ce-42ea-b729-0b9fd2e28c4d

P.n.nesarajan, M.venkatachalam, T.ranganayaki . A Novel Web Optimization Technique using Enhanced Particle Swarm Optimization. National Conference on Research Issues in Image Analysis and Mining Intelligence. NCRIIAMI2015, 1 (June 2015), 28-32.

@article{
author = { P.n.nesarajan, M.venkatachalam, T.ranganayaki },
title = { A Novel Web Optimization Technique using Enhanced Particle Swarm Optimization },
journal = { National Conference on Research Issues in Image Analysis and Mining Intelligence },
issue_date = { June 2015 },
volume = { NCRIIAMI2015 },
number = { 1 },
month = { June },
year = { 2015 },
issn = 0975-8887,
pages = { 28-32 },
numpages = 5,
url = { /proceedings/ncriiami2015/number1/21021-4012/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Research Issues in Image Analysis and Mining Intelligence
%A P.n.nesarajan
%A M.venkatachalam
%A T.ranganayaki
%T A Novel Web Optimization Technique using Enhanced Particle Swarm Optimization
%J National Conference on Research Issues in Image Analysis and Mining Intelligence
%@ 0975-8887
%V NCRIIAMI2015
%N 1
%P 28-32
%D 2015
%I International Journal of Computer Applications
Abstract

Web performance is very important. One way to improve performance is through caching. But caching is already widely used, and studies suggest that much of the theoretically achievable performance from caching is already being realized. Caching has reduced bandwidth consumption and downloads latency. On the other hand, web-caching is heavy to enlarge further due to the developing amount of non-cacheable dynamic web-documents. Increasing the performance of web is an essential requirement, because its result in a huge increase in user supposed latency. This neat source of information establishes a basis for observations that can lead to improved overall performance for a given Web site. The main limitation focused in this method is to find out the optimal cache memory that should be keeping in order achieving maximum cost effectiveness. This method utilizes a successful Great Deluge algorithm based Particle Swarm Optimization (GDPSO) approach for achieving the best cache memory size which in turn decreases all the network cost. The investigation shows that hierarchical distributed caching can save important network cost through the use of the GDPSO algorithm.

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Index Terms

Computer Science
Information Sciences

Keywords

Website Optimization Techniques Web Performance Particle Swarm Optimization (pso) Great Deluge Particle Swarm Optimization (gdpso)