Tuning of fuzzy models by fuzzy neural networks
Fuzzy Sets and Systems
Capacity planning for Web performance: metrics, models, and methods
Capacity planning for Web performance: metrics, models, and methods
A client-aware dispatching algorithm for web clusters providing multiple services
Proceedings of the 10th international conference on World Wide Web
The state of the art in locally distributed Web-server systems
ACM Computing Surveys (CSUR)
Web switch support for differentiated services
ACM SIGMETRICS Performance Evaluation Review
Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis
IEEE Transactions on Computers
Fuzzy-neural web switch supporting differentiated service
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Using adaptive fuzzy-neural control to minimize response time in cluster-based web systems
AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Global Distribution of HTTP Requests Using the Fuzzy-Neural Decision-Making Mechanism
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Adaptive scheduling system guaranteeing web page response times
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
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This paper presents the application of fuzzy logic and neural networks to HTTP request dispatching performed within a geographically distributed Web system. Web sites serve as a global content delivery system where each Web server can respond to the client request. We propose broker-based system architecture with a global request dispatching algorithm called GARDiB. The algorithm uses the fuzzy-neural decision-making mechanism to assign each incoming request to the server with the least expected response time. The response time include the transmission time over the network, both for the request and for the response, as well as the time elapsed on the server responding to the request. We demonstrate through the simulations that our algorithm is more effective than popular global dispatching policies Round-Robin and Weighted Round-Robin.