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

• Autorzy: Krzysztof Zatwarnicki
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

neuro-fuzzy model; request distribution; Web cluster; QoWS

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2012
• Tom: 22
• Numer: 2
• Strony: 365-377

Daty

wydano

2012

otrzymano

2011-03-03

poprawiono

2011-08-12

poprawiono

2011-09-28

Twórcy

autor

Krzysztof Zatwarnicki

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

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Identyfikatory

DOI

10.2478/v10006-012-0027-4