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2012 | 22 | 2 | 365-377

Tytuł artykułu

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

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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.

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


  • AlSa'deh, A. and Yahya, A.H. (2008). Shortest remaining response time scheduling for improved web server performance, in J.Filipe and J. Cordeiro (Eds.), Web Information Systems and Technologies, Lecture Notes in Business Information Processing, Vol. 18, Springer-Verlag, Berlin/Heidelberg, pp. 80-92.
  • Andreolini, M., Casolari, S. and Colajanni, M. (2008). Autonomic request management algorithms for geographically distributed internet-based systems, Proceedings of the 2nd IEEE International Conference on Self-Adaptive and SelfOrganizing Systems, Venezia, Italy, pp. 171-180.
  • Barford, P., Bestavros, A., Bradley, A. and Crovella, M. (1999). Changes in web client access patterns: Characteristics and caching implications, World Wide Web 2(1): 15-28.
  • Borzemski, L. (2006). The use of data mining to predict web performance, Cybernetics and Systems 37(6): 587-608.
  • Borzemski, L. and Suchacka, G. (2010). Business-oriented admission control and request scheduling for e-commerce websites, Cybernetics and Systems 41(8): 592-609.
  • Borzemski, L. and Zatwarnicki, K. (2003). A fuzzy adaptive request distribution algorithm for cluster-based web systems, 11th Euromicro Workshop on Parallel, Distributed and Network-Based Processing, PDP 2003, Genoa, Italy, pp. 119-126.
  • Borzemski, L. and Zatwarnicki, K. (2006). Fuzzy-neural web switch supporting differentiated service, in B. Gabrys, R.J. Howlett and L.C. Jain (Eds.), Knowledge-Based Intelligent Information and Engineering Systems, Lecture Notes in Artificial Intelligence, Vol. 4252, Springer-Verlag, Berlin/Heidelberg, pp. 195-203.
  • Borzemski, L., Zatwarnicki, K. and Zatwarnicka, A. (2007). Adaptive and intelligent request distribution for content delivery networks, Cybernetics and Systems 38(8): 837-857.
  • Cardellini, V., Casalicchio, E., Colajanni, M. and Mambelli, M. (2001). Web switch support for differentiated services, ACM Performance Evaluation Review 29(2): 14-19.
  • Cardellini, V., Casalicchio, E., Colajanni, M. and Yu, P.S. (2002). The state of the art in locally distributed web-server systems, ACM Computing Surveys 34(2): 263-311.
  • Casalicchio, E. and Colajanni, M. (2001). A client-aware dispatching algorithm for web clusters providing multiple services, Proceedings of the 10th International World Wide Web Conference, Hong Kong, China, pp. 535-544.
  • Cherkasova, L. and Karlsson, M. (2001). Scalable webserver cluster design with workload-aware request distribution strategy ward, Proceedings of the 3rd International Workshop on Advanced Issues of e-Commerce and Web-Based Information Systems (WECWIS), Washington, DC, USA, p. 212.
  • CSIM (2008). Mesquite software 2008: Development toolkit for simulation and modeling,
  • Driankov, D., Hellendoorn, H. and Reinfrank, M. (1996). An Introduction to Fuzzy Control, Springer, New York, NY.
  • Elnikety, S., Nahum, E., Tracey, J. and Zwaenepoel, W. (2004). A method for transparent admission control and request scheduling in e-commerce web sites, WWW'04: Proceedings of the 13th International Conference on World Wide Web, New York, NY, USA, pp. 276-286.
  • Gilly, K., Juiz, C. and Puigjaner, R. (2011). An up-to-date survey in web load balancing, World Wide Web 14(2): 105-131.
  • Harchol-Balter, M., Schroeder, B., Agrawal, M. and Bansal, N. (2003). Size-based scheduling to improve web performance, ACM Transactions on Computer Systems 21(2): 207-233.
  • Horikowa, S., Furuhashi, T. and Uchikawa, Y. (1992). On fuzzy modeling using fuzzy neural networks with the backpropagation algorithm, IEEE Transactions on Neural Networks, Los Alamitos, CA, USA, pp. 801-806.
  • Kwok, Y.-K. and Cheung, L.-S. (2004). A new fuzzy-decision based load balancing system for distributed object computing, Journal of Parallel and Distributed Computing 64(2): 238-253.
  • Kun-Ming, V., Chou, Y. and Wang, Y. (2004). A fuzzy-based dynamic load-balancing algorithm, Journal of Information, Technology and Society 4(2): 55-63.
  • Lee, K.M., Kwak, D.H. and Leekwang, H. (1995). Tuning of fuzzy models by fuzzy neural networks, Fuzzy Sets and Systems 76(1): 47-61.
  • Lee, S.C.M., Lui, J.C.S. and Yau, D.K.Y. (2004). A proportionaldelay diffserv-enabled web server: Admission control and dynamic adaptation, IEEE Transactions on Parallel and Distributed Systems 15(5): 385-400.
  • Mamdani, E. H. (1977). Application of fuzzy logic to approximate reasoning using linguistic synthesis, IEEE Transactions on Computers C-26(12): 1182-1191.
  • Menasce, D. and Almeida, V. (1998). Capacity Planning for Web Performance. Metrics, Models, and Methods, PrenticeHall, New York, NY.
  • Pai, V.S., Aron, M., Banga, G., Svendsen, M., Druschel, P., Zwaenepoel, W. and Nahum, E. (1998). Locality-aware request distribution in cluster-based network servers, ACM SIGPLAN Notices 33(11): 205-215.
  • Pilinski, M. (1996). Universal network trainer, Proceedings of the 2nd Conference on Neural Networks and Their Applications, Częstochowa, Poland, Vol. 2, pp. 383-391.
  • Quan, Z. and Chung, J.-M. (2005). Statistical admission control for real-time services under earliest deadline first scheduling, Computer Networks 48(2): 137-154.
  • Riska, A., Sun, W., Smirni, E. and Ciardo, G. (2002). Adaptload: Effective balancing in clustered web servers under transient load conditions, 22nd International Conference on Distributed Computing Systems (ICDCS 2002), Vienna, Austria, pp. 103-111.
  • Simiński, K. (2010). Rule weights in a neuro-fuzzy system with a hierarchical domain partition, International Journal of Applied Mathematics and Computer Science 20(2): 337-347, DOI: 10.2478/v10006-010-0025-3.
  • Wei, J. and Xu, C.-Z. (2006). Provisioning of client-perceived end-to-end QoS guarantees in web servers, IEEE Transactions on Computers 55(12): 1543-1556.
  • Wei, J., Zhou, X. and Xu, C.-Z. (2005). Robust processing rate allocation for proportional slowdown differentiation on internet servers, IEEE Transactions on Computers 54(8): 964-977.
  • Williams, A., Arlitt M., Williamson, C. and Barker, K. (2005). Web workload characterization: Ten years later, in X. Tang, I. Xu and S.T. Chanson (Eds.), Web Content Delivery, Web Information Systems Engineering and Internet Technologies, Vol. 2, Springer-Verlag, Berlin/Heidelberg, pp. 3-21.
  • Xia, C.H., Liu, Z., Squillante, M.S., Zhang, L. and Malouch, N. (2005). Web traffic modeling at finer time scales and performance implications, Performance Evaluation 61(2): 181-201.
  • Zadeh, L.A. (1965). 8(3): 338-353.
  • Zadeh, L. A. (1996). Fuzzy logic-computing with words, IEEE Transactions on Fuzzy Systems 4(2): 104-111.
  • Zatwarnicki, K. (2010). Neuro-fuzzy models in global HTTP request distribution, in J. Pan, S. Chen and N.T. Nguyen (Eds.), Computational Collective Intelligence, Lecture Notes in Computer Science, Vol. 6421, Springer-Verlag, Berlin/Heidelberg, pp. 1-10.
  • Zatwarnicki, K. (2011). Identification of the Web server, in A. Kwiecień, P. Gaj and P. Stera (Eds.), Computer Networks, Communications in Computer and Information Science, Vol. 160, Springer-Verlag, Berlin/Heidelberg, pp. 45-54.
  • Zhou, X., Wei, J. and Xu, C.-Z. (2007). Quality-of-service differentiation on the internet: A taxonomy, Journal of Network and Computer Applications 30(1): 354-383.

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