A Cognizant agent system for optimizing cloud service searching strategy

Abstract

Cloud service searching technique is used to find relevant information on World Wide Web. Each search engine maintains following process in real time environment like web crawling, web scrapping, indexing and searching. The search engine over cloud is specially designed for cloud service discovery. This search engine mainly concentrates on discovering appropriate cloud services in effective and efficient manner. We proposed a technique named as Cognizant Clustering Algorithm that group service entries based on cloud user requirements that include functional, technical and cost specification. This search engine uses a similarity ontology that provides interrelationships between service entries. The similarity ontology has three kind of operation over cloud that includes perception, object entity and data type similarity reasoning. It uses Cognizant clustering matrix to calculate the number of service entries, distance and utilization per request. It improves the search result more effective and significantly increases the performance in service discovery over cloud environment.