TRUST MODEL FOR CLOUD AND GRID ENVIRONMENT USING FUZZY LOGIC AND ARTIFICIAL NEURAL NETWORK

Abstract

Cloud Computing is a technology which offers various on-demand services such as software, platform, and infrastructure required by the clients. Grid Computing is a process of allotting the resources required to solve complex problems. In cloud or grid environment the service providers provides the services/resources to the clients. In this regard the service providers need to maintain and manage trust for further proceedings. This research article proposed a trust model using Fuzzy Logic and Artificial Neural Network (ANN) applicable for both cloud and grid environment. The Fuzzy Logic is used to remove the impreciseness of the data. The decision derived by using Fuzzy Logic lies between zero (0) to one (1) that represents the continuous values, where 0 is the lowest and 1 is the highest value in decision making. In this article Fuzzy Logic is used to generate the trust value based on the fuzzy rules by accepting the given inputs of six parameters namely reliability, response time, fault tolerance, security, elasticity, and service level agreement (SLA). Then based on the generated trust value the service provider is allotted to the clients. Artificial Neural Network is a prediction model used to predict the trust value of the service provider based on the same six parameters mentioned as input for Fuzzy Logic. Based on the predicted trust value the service provider is allotted to the client. This article shows the experiments and results based on the Fuzzy Logic Model and Artificial Neural Netwok Model for the process of service provider allottment. The experiments and results worked on the dataset of 20000 instances collected from the authenticated source.