An effective analysis on various scheduling algorithms in cloud computing

Cloud Computing focuses on demand services to the customers as pay-as-you go model with different Service level agreements at different levels. Most of the cloud services run with virtual machines. In this scenarios task scheduling plays an important role to schedule the tasks in an effective manner. The existing scheduling algorithms have the limitations like less memory utilization, high execution time, and high response time. These limitations in existing algorithms lead to inadequate load balance in dynamic situations, and provide the resource inefficient manner. In this paper, we have studied wide range of existing scheduling algorithms in cloud computing with respect to new metrics such as average migration time and electricity price per unit cost which are missing in existing studies, also studied conventional performance metrics like Response time, makespan, QOS, Memory utilization and Response time. Eventually, we have done the comparison study on existing scheduling algorithms and based on our study we identify the new research direction in the cloud scheduling algorithms.