A novel intelligence request dispatcher algorithm for Web server clusters

Summary form only given. In this paper we propose a new scheduling policy namely IRD (intelligence request dispatcher) for Web switches operating at layer-7 of OSI protocol stack in a Web server farm. We classify dynamic and static requests. A hybrid neuro-fuzzy and LARD like approach is used to make route decision of dynamic and static requests separately. IRD selects the server with lower response time in an adaptive dispatching policy. In particular, we used the ANFIS (adaptive neuro fuzzy inference system) methodology to build a Sugeno fuzzy model to assign each incoming dynamic request to the server with the least expected response time. This estimation is based on expected impact of each client´s individual request on server resources. These resources are: number of connections, CPU and disk usage. These parameters are used to evaluate load-weight of each server in a fuzzy manner and retrieve through feedback. For static requests an algorithm used to improve the cache hit rate in Web cluster nodes according to their load-weights. Its goal is to improve load sharing in Web clusters with dynamic and static information. Prototype implementation results confirm that the proposed algorithm is more effective than representative request distribution algorithms, especially for dynamic requests that require sophisticated policy and more service time than static information.