Enhanced Network Traffic Classification through Priority Based User Scheduling Algorithm (PUSA)

Abstract

The Most colleges and universities are embracing new technologies that can deliver powerful resources with ease of use. Cloud computing is one of the smart technologies they are using. It is a new paradigm that can provide on-demand services such as servers, storage disks, platforms and applications to any cloud service customers over a network. To address both issues, efficient task scheduling optimization methods must be provided.

 Task scheduling algorithms are one of the major theoretical challenges in the field of network classification and scheduling. Some intensive researches have been done in the field of task scheduling of cloud figures. In this paper, we proposed a new algorithm for priority classification and user scheduling in cloud computing. The proposed algorithm is based on a decision making model with multiple criteria to use the supervised machine learning classification algorithms to classify the priority tasks into priorities User Scheduling (PUS) different tasks priority queue to improve the task scheduling response time A users scheduling algorithm task in a multi-class network is also to categorize the users into one of the predefined classes. Since this approach has more users and the parameters considered for classification are more independent, simulation results suggest that the classification technique clusters the task more effectively and provides consistent use of available resources.