Advanced Cloud based Task Scheduling Architecture to Optimize Performance in Datacenter

Abstract

In cloud datacenter, job scheduling is used to manage real-time user data for improving response time of user query. Completion of tasks depends on datacenter availability, the capacity of virtual machines, network connection, and broker management policies. We propose a cloud-based architecture with a cloud service manager to select virtual machines from vmpool for optimizing tasks in the datacenter. The scheduling algorithm decides which virtual machine executes the task according to the nature and size of the task with minimal waiting time for execution.