QoS Aware Group-Based Workload Scheduling in Cloud Environment

Abstract

Cloud computing paradigm provides dynamically scalable resources as a service over the Internet. It promises reduction in capital expenditure as well as operational expenditure. In cloud computing, there are still some challenges need to be solved. Among them, job scheduling is one of the important issues, since the objective of service provider and the cloud user is to utilize the computing resources efficiently. Job scheduling is the process of assigning user jobs to appropriate resources so that it can utilize the cloud resources efficiently. In cloud computing environment, the communication time between the users and resources can have a great impact on job scheduling. The primary objective in cloud environment is to process the tasks provided by user with higher responsiveness. So there is a need of an efficient group-based job scheduling algorithm that assemble the independent fine-grained jobs into groups by taking the communication time into consideration. In this work, we have proposed a group-based scheduling strategy for scheduling fine-grained jobs according to the processing capability and bandwidth of available resources in cloud computing environment.