Implementation of K-means clustering for evaluating SaaS on the cloud computing environment
DHANAMMA SHANKAR JAGLI, Seema Uday Purohit, Subash Chandra Nalla · 2016
The current trend in the technology have been drastically changed. The usage of latest technology, cloud computing become a central attraction in everywhere for sharing resources. Software as a Service (SaaS) is the most important part of cloud computing, it can be used for providing various business solutions. In the real world, many organizations had successfully implemented this concept. Henceforth demand for Software as a Service (SaaS) has been tremendously increased by end users as well as by a service provider, but still, it is a big challenging task for cloud service providers to evaluate their services, provided to the end user. It is also difficult for end users to find out the potential software services in the cloud computing environment. In this paper, the solution for evaluating SaaS quality attributes is provided by using K-means clustering algorithm. This paper initially, describes the motivation for evaluating SaaS on the cloud-computing environment with the problem description. Secondly, it's describing the various issues and challenges for evaluating software services on the cloud computing. Thirdly, it explains about the proposed work in evaluating Software as a Service. Finally, the solution to the identified problem is implemented and analyzed the results.