Discovery of resources over Cloud using MADM approaches

Sa？etak Cloud and P2P computing allows the sharing of resources among its users from diverse geographical locations. The resources are heterogeneous in nature and possess distinct attributes. The majority of the existing techniques rely on the static attributes during resource selection. However, the matching of resources based on static attributes may not be the best for the execution of user jobs. The resources could be very attractive as per the static configuration but might be heavily loaded with other multiple jobs since the working memory and storage space might have already been utilized. Hence, there is a need to consider the dynamic state of the resources in order to locate the most suitable resources for user jobs. In this paper, a 2-phased multi-attribute decision making (MADM) mechanism is proposed to locate the appropriate resources. The first phase explains a mechanism to discover all the matched resources and the second phase then applies the PROMETHEE MADM approach on the set of resources to find the most suitable resource for the user job. The proposed approach enables users to find the most suitable resource for their respective jobs