FUZZY INFERENCE SYSTEM BASED REPUTATION MODEL FOR GRID ENVIRONMENT

Abstract

Grid Computing enables the secured, controlled and flexible sharing of resources among various dynamically created virtual organizations. These virtual organizations are setup for collaborative problem solving that requires a great number of processing cycles. Grid computing provides highly scalable, highly secure and utmost high performance mechanisms for discovering and negotiating access to the . computing resources among an infinite number of geographically distributed groups to solve complex scientific or technical problems. Development of grid computing enforces the implementations of economic and efficient models, though the assumptions are there that both transaction parties are honest and trustworthy. In reality there is serious information asymmetry between transacting entities . Introducing trust and reputation can solve this problem to a great extent though the issue which is related with reputation and trust is it's imprecise nature which makes it difficult to be determined by precise conventional mathematics. In this dissertation I have focussed on a Fuzzy Inference System based Reputation model that will provide a previous experience based custom rule-setting to determine reputation for a transacting party. Malicious recommendations in indirect trust transmission has been also removed and punished in this model . The design and simulation of the controller is done using GridSim and the simulation results are presented to demonstrate the efficiency of the Fuzzy Inference System Based Reputation Model (FISRM). The experimental results on different type of fraudulent users shows its stability and steady performance over the conventional Reputation Based Allocation Model(RBAM).