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Grid computing is the next generation of distributed system. Its goal is to create a huge, independent and powerful virtual machine, and it has been created by gathering different machines with the aim of sharing them. Resource discovery is the most fundamental phase of resource management which has been considered in our work. Considering the advantages and disadvantages of P2P and grid and their architectural similarity; using some of P2P approaches as a solution in Grid can improve the performance of Grid. Semantic technology and fuzzy logic are the two intelligent approaches, which recently apply on P2P network and Grid environment. In P2P networks, nodes are grouping based on their interests. Moreover semantic can be very useful for grouping nodes. This paper follows the identification of resource discovery in grid environment with the help of semantic and fuzzy theory and seeking to present a resource discovery algorithm with respect to exiting obstacles. The proposed approach is assessed in simulated grid environment and the results are compared with other approaches in same conditions. The goals of our approach are to obtain precious matching by clustering nodes which have services semantically related, improving search expressiveness by considering the distances between nodes (delay) in clustering phase, and decreasing response time and processing time by considering the nodes computational capabilities and free space of each node. We evaluate the performance of our approach with some distributed semantic based grid resource discovery models. The results of the experiments show the efficiency of the proposed approach in term of scalability, precision, search expressiveness and response time.
Javanmardi et al. (Mon,) studied this question.