<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>A significant development of Web technologies requires the application of more and more complex systems and algorithms for maintaining high quality of Web services. Presently, not only simple decision-making tools but also complex adaptation algorithms using artificial intelligence techniques are applied for controlling HTTP request traffic. The paper presents a new LFNRD (Local Fuzzy-Neural Adaptive Request Distribution) algorithm for request distribution in cluster-based Web systems using neuro-fuzzy models of Web servers in the decision-making process. The neuro-fuzzy model which is applied is discussed in detail and a design of the Web switch using the proposed solution is presented. Finally, a testbed is described and the results of a comparative simulation study on the LFNRD algorithm, and other algorithms known from the literature and used in the industry, are presented and discussed.</p></abstract>

A significant development of Web technologies requires the application of more and more complex systems and algorithms for maintaining high quality of Web services. Presently, not only simple decision-making tools but also complex adaptation algorithms using artificial intelligence techniques are applied for controlling HTTP request traffic. The paper presents a new LFNRD (Local Fuzzy-Neural Adaptive Request Distribution) algorithm for request distribution in cluster-based Web systems using neuro-fuzzy models of Web servers in the decision-making process. The neuro-fuzzy model which is applied is discussed in detail and a design of the Web switch using the proposed solution is presented. Finally, a testbed is described and the results of a comparative simulation study on the LFNRD algorithm, and other algorithms known from the literature and used in the industry, are presented and discussed.

Adaptive control of cluster-based Web systems using neuro-fuzzy models

Department of Electrical, Control and Computer Engineering, Opole University of Technology, ul. Sosnkowskiego 31, 45-272 Opole, Poland

International Journal of Applied Mathematics and Computer Science

{"article-title":"Adaptive control of cluster-based Web systems using neuro-fuzzy models"}

A significant development of Web technologies requires the application of more and more complex systems and algorithms for maintaining high quality of Web...

Adaptive control of cluster-based Web systems using neuro-fuzzy models

Data publikacji: 28 cze 2012

Zakres stron: 365 - 377

DOI: https://doi.org/10.2478/v10006-012-0027-4

Słowa kluczowe
neuro-fuzzy model, request distribution, Web cluster, QoWS

This content is open access.

Adaptive control of cluster-based Web systems using neuro-fuzzy models

Data publikacji: 28 cze 2012

Zakres stron: 365 - 377

DOI: https://doi.org/10.2478/v10006-012-0027-4

Słowa kluczoweneuro-fuzzy model, request distribution, Web cluster, QoWS

This content is open access.

Słowa kluczowe
neuro-fuzzy model, request distribution, Web cluster, QoWS