Development of SLA Monitoring Tools Based on Proposed DMI in Cloud Computing

Abstract

As there is an enormous amount of online research material available, finding pertinent information for specific purposes has become a tedious chore. So there is a requirement of the research paper recommendation system to facilitate research scholars in finding their interested and relevant research papers. There are many paper recommendation systems available, most of them are depending on paper assemblage, references, user profile, mind maps. This information is generally not easily available. The majority of the prevailing recommender system is based on collaborative filtering that rely on other user's proclivity. On the other hand, content-based methods use information regarding an item itself to make a recommendation. In this paper, we present a research paper recommendation method that is based on single paper. Our method uses content-based recommendation approach that employs information extraction and text categorization. . It performs the profile learning by using naive Bayesian text classifier and generates recommendation on the basis of an individual's preference.

Cloud Monitoring Data Challenges: A Systematic Review

“…software as a service, platform as a service, infrastructure as a service) to enable business agility and flexibility [10]. Cloud computing seems to offer lucrative benefits [3], however, organizations need to actively monitor and analyze the operational data about the quality of cloud services and utilization of underlying virtual resources such as CPU, memory, storage and network [6]. This is also important to verify and identify any service performance related issues including Service Level Agreement (SLA).…”