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

Krzysztof Zatwarnicki

International Journal of Applied Mathematics and Computer Science (2012)

  • Volume: 22, Issue: 2, page 365-377
  • ISSN: 1641-876X

Abstract

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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.

How to cite

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Krzysztof Zatwarnicki. "Adaptive control of cluster-based Web systems using neuro-fuzzy models." International Journal of Applied Mathematics and Computer Science 22.2 (2012): 365-377. <http://eudml.org/doc/208114>.

@article{KrzysztofZatwarnicki2012,
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.},
author = {Krzysztof Zatwarnicki},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {neuro-fuzzy model; request distribution; Web cluster; QoWS; web cluster; quality of Web services (QoWS)},
language = {eng},
number = {2},
pages = {365-377},
title = {Adaptive control of cluster-based Web systems using neuro-fuzzy models},
url = {http://eudml.org/doc/208114},
volume = {22},
year = {2012},
}

TY - JOUR
AU - Krzysztof Zatwarnicki
TI - Adaptive control of cluster-based Web systems using neuro-fuzzy models
JO - International Journal of Applied Mathematics and Computer Science
PY - 2012
VL - 22
IS - 2
SP - 365
EP - 377
AB - 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.
LA - eng
KW - neuro-fuzzy model; request distribution; Web cluster; QoWS; web cluster; quality of Web services (QoWS)
UR - http://eudml.org/doc/208114
ER -

References

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