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
Content Networking: Architecture, Protocols, and Practice (The Morgan Kaufmann Series in Networking)
Content Networking: Architecture, Protocols, and Practice (The Morgan Kaufmann Series in Networking)
Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis
IEEE Transactions on Computers
ADAPTIVE AND INTELLIGENT REQUEST DISTRIBUTION FOR CONTENT DELIVERY NETWORKS
Cybernetics and Systems
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
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
Neuro-fuzzy models in global HTTP request distribution
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume PartI
| Hi-index | 0.00 |
This paper presents the application of fuzzy logic and neural networks to HTTP request dispatching performed within Content Delivery Network. We propose a global request distribution algorithm called GARD to support request routing to the surrogate servers that deliver the requested content in an efficient manner. 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 dispatching policies as Round-Robin and Weighted Round-Robin. We also show that in case of non-evenly loaded environment the GARD algorithm outperforms RTT algorithm which is often used in CDNs.