Machine Learning based Presaging Technique for Multi-user Utility Pattern Rooted Cloud Service Negotiation for Providing Efficient Service
B.Udaya Kumar, Ayngaran Krishnamurhty, R. Madhan Mohan · 2020
In recent years, Cloud computing is emerging as an indispensable technology in handling the increasing number of users and data generated by them. Despite the hype, the increasing data rate proportionally increases the workload of the cloud service providers in order to meet the consumer demands. Moreover this situation results in developing many cloud service providers in order deliver the required and efficient services to the users. But the way to select the appropriate service provider is still remaining as a bottleneck. To solve the increasing server negotiation challenges, a pattern-based service negotiation method has been utilized in this research work. This method has been implemented with an improved suggestion feature, which provides users with similar patterns recognized form their past entries to assist the users with their current selection. By incorporating implicit tracking approach, a sequence of the services accessed by the users have been maintained and this can be leveraged as suggestion to the users. Based on the pattern, the most important services are ranked according to the users' activity and the data has been observed using machine learning algorithm. The ranked list is given to the user to select the required service. The proposed technique increases the performance of the cloud environment and also the strain handled by the service provider in suggesting the utility pattern for the user is reduced by using the machine learning concept.