Fuzzy Analytical Hierarchy Process Based Optimal Work Station node prediction for Large Networks

Abstract

Cloud Computing is an emerging computing technology and delivering lots of services to the end users. In order to ensure the quality of cloud service, the service request ought to be ready to dynamically predict the optimal work station node. The research proposes an optimal work station node prediction in Hierarchical large networks using Fuzzy Analytical Hierarchical Process (AHP). This work is considered as a hierarchical model to explore each level and their sublevel based on the resource availability. The prediction of optimal workstation is dogged on the resource factors: Energy, Memory and Cost. Each work station periodically determines these factors with sub level work stations. The advantage of the proposed work is to predict the best workstation to serve an efficient cloud service for large networks. The proposed model simulated by using MATLAB tool, experiments has been conducted to prove the appropriateness of this novel approach.