Dynamic Task Scheduling in Cloud Computing Based on Naïve Bayesian classifier

چکیده مقاله

the issue of task scheduling in a cloud environment is one of the most important issues that must be considered by the cloud platform providers in data centers. The use of the right solution to solve this problem enables cloud platform providers to have the most use of available resources; and also increase the customer satisfaction by providing quality of service parameters. In this paper it has been tried to provide a dynamic scheduling algorithm using machine learning techniques and naïve-Bayes classifier in a cloud environment. The proposed method is one of the dynamic task scheduling methods and load distribution at any moment is conducted according to the latest information from previous and current server status. The distinction of this method with previous studies is the use of data mining techniques (classification) in load distribution. Since this classification method has higher accuracy and speed compared with other methods, therefore this classifier helps us to achieve the optimal solution in less time. Simulation results show that the proposed method has a good improvement in terms of Makespan time and load balancing degree.