Scheduling to maximize the data transfer rate for big data applications in cloud system

Abstract

In cloud platform, parallel computing is precisely one of the methods to handle various computational tasks which need to perform fast on a large dataset. In a system each job was run by the respective processors. Jobs may need to be accompanying through nodes and it will share resources. So scheduling is important to share the resources and path diversity is very much of important in order to get the data within least retrieval time. The existing scheduling algorithms should not efficiently find the optimum solution. In this paper we make a survey to provide the better transfer scheduling algorithm for transfer the data within stipulated time, to maximize the data transfer rate and to choose cost effective paths.