Numerical Similarity Algorithms for Cloud Service Discovery and Selection System
Samer Hasan, V. Valli Kumari · International journal of intelligent engineering and systems · 2017
Cloud computing delivers computing services over the Internet based on pay as you use financial model.Cloud service providers publish service advertisements in different formats on the Internet.Thus, cloud consumers should explore all provider websites using available search engines to find the appropriate cloud service.Unfortunately, existing search engines give a huge list of unrelated results that makes consumers spend a lot of time and effort to find the best matched cloud service.In this paper, we present a layered architecture for cloud service discovery and selection system to automate cloud service discovery and selection process, and remove the barriers between cloud service providers and consumers.Additionally, we present novel numerical algorithm for cloud services matching and compare it with existing algorithms.Proposed algorithm (XNSim) is independent of any external attribute value, while existing algorithm (SNSim) depends on the max and min values of the service attribute and (MNSim) algorithm depends on the max value of the service attribute.Comparison is done based on four parameters (number of matched services, execution time, average score and recall) to find the advantages and disadvantages of each one.XNSim algorithm showed better performance and more effectiveness over MNSim and SNSim.