Abstract
This work presents the application of two adaptive decision making algorithms in Web switch controlling operations of cluster-based Web systems. The proposed approach applies machine learning techniques; namely a fuzzy logic and neural networks, to deploy the adaptive and intelligent dispatching within locally distributed fully replicated Web servers. We present the adaptive control framework and the design of Web switch applying our conception. We demonstrate through the simulations experiments the difference between our algorithms and compare them with the most popular and reference distribution algorithms.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Aron, M., Sanders, D., Druschel, P., Zwaenepoel, W.: Scalable content-aware request distribution in cluster-based network servers. In: Proc. of USENIX 2000 Conf., USA (2000)
Barford, P., Crovella, M.E.: A Performance Evaluation of Hyper Text Transfer Protocols. In: Proc. ACM SIGMETRICS 1999, Atlanta, pp. 188–197 (1999)
Borzemski, L., Zatwarnicki, K.: A Fuzzy Adaptive Request Distribution algorithm for cluster-based Web systems. In: 11th Euromicro Workshop on Parallel, Distributed and Network-Based Processing (PDP 2003), pp. 119–126 (2003)
Borzemski, L., Zatwarnicki, K., Zatwarnicka, A.: Adaptive and Intelligent Request Distribution for Content Delivery Networks. Cybernetics and Systems 38(8), 837–857 (2007)
Bubnicki, Z.: Modern Control Theory. Springer, Berlin (2005)
Cardellini, V., Casalicchio, E., Colajanni, M., Yu, P.S.: The state of the art in locally distrib-uted Web-server systems. ACM Computing Surveys 34(2), 263–311 (2002)
Casalicchio, E., Colajanni, M.: A Client-Aware Dispatching Algorithm for Web Clusters Providing Multiple Services. In: Proc. of the10th International World Wide Web Conference, Hong Kong (2001)
Choi, E.: Performance test and analysis for an adaptive load balancing mechanism on distributed server cluster systems. Future Generation Systems 20, 237–247 (2004)
Gilly, K., Juiz, C., Puigjaner, R.: An up-to-date survey in web load balancing. Springer, Heidelberg (2010), World Wide Web, 10.1007/s11280-010-0101-5
Mesquite Software Inc. CSIM User’s Guide, Austin, TX (2010), http://www.mesquite.com
Werbos, P.: Beyond regression: New tools for prediction and analysis in the behavioral sciences, Ph.D. dissertation, Committee on Appl. Math., Cambridge (1974)
Zatwarnicki, K.: Providing Web Service of Established Quality with the Use of HTTP Requests Scheduling Methods. In: Jędrzejowicz, P., Nguyen, N.T., Howlet, R.J., Jain, L.C. (eds.) KES-AMSTA 2010. LNCS (LNAI), vol. 6070, pp. 142–151. Springer, Heidelberg (2010)
Zhang, Q., Riska, A., Sun, W., Smirni, E., Ciardo, G.: Workload-aware load balancing for clustered web servers (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zatwarnicki, K. (2011). Adaptive Request Distribution in Cluster-Based Web System. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23851-2_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-23851-2_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23850-5
Online ISBN: 978-3-642-23851-2
eBook Packages: Computer ScienceComputer Science (R0)