Enhancing Greedy Web Proxy caching using Weighted Random Indexing based Data Mining Classifier

Title

Enhancing Greedy Web Proxy caching using Weighted Random Indexing based Data Mining Classifier

Creator

Pernabas J.B.; Fidele S.F.; Vaithinathan K.K.

Description

Web Proxy caching system is an intermediary between the Web users and servers that try to alleviate the loads on the origin servers by caching particular Web objects and behaves as the proxy for the server and services the requests that are made to the servers. In this paper, the performance of a Proxy system is measured by the number of hits at the Proxy. Higher number of hits at the Proxy server reflects the effectiveness of the Proxy system. The number of hits is determined by the replacement policies chosen by the Proxy systems. Traditional replacement policies that are based on time and size are reactive and do not consider the events that will possibly happen in the future. The performance of the web proxy caching system is improved by adapting Data Mining Classifier model based on Web User clustering and Weighted Random Indexing Methods. The outcome of the paper are proactive strategies that augment the traditional replacement policies such as GDS, GDSF, GD? which uses the Data Mining techniques. 2019

Source

Egyptian Informatics Journal, Vol-20, No. 2, pp. 117-130.

Date

2019-01-01

Publisher

Elsevier B.V.

Subject

Clustering; Data Mining; GD^? ; GDS; GDSF; Proxy; Random indexing

Coverage

Pernabas J.B., Department of Computer Science and Engineering, Faculty of Engineering, CHRIST(Deemed To be University), Kengeri Campus, Kanmanike, Bangalore, 560074, Karnataka, India; Fidele S.F., Department of Computer Science and Engineering, Pondicherry Engineering College, ECR, Pillaichavady, Pondicherry, 605014, India; Vaithinathan K.K., Department of Computer Engineering, Karaikal Polytechnic College, Varichikudy, Karaikal-609609, India

Rights

All Open Access; Gold Open Access

Relation

ISSN: 11108665

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1016/j.eij.2019.01.001

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