Dynamic load balancing algorithm based on deadline constrained in cloud environment

The Performance of cloud depends on the task scheduling as well as load balancing. Cloud Service Provider (CRP) provides services on demand to the users, as the application as well as the numbers of users are gradually growing over the cloud environment which leads to the increasing in the workload that are deployed over the virtual machine (VM). Due to the growing in traffic as well as workload, there is need for the cloud resource broker to have effective as well as efficient algorithm that disseminate task properly within the entire running VM, also decreases the rejection ratio of the task. This research work implements a scheduling algorithm which balances the workload among the whole VM using last K interval and to measure makespan time as well as number task that meet their respective deadline when the resources and task rejection is increasing. An experiment was carried out using Cloudsim Simulator. The results show that makespan time was reduce and improves the ratio of task that will meeting to their respective deadline when compared with the First Come First Serve (FCFS), Dynamic Min-Min, and Shortest Job First (SJF) algorithm.

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