An Improved Longest Approximate Time to End Algorithm using Dynamic Cloud Sim

Longest approximate time to end scheduling algorithm sorts all the cloud jobs in queue according to their time taken in execution and other time base performance parameters. However, in many ways for scheduling analysis, planning makes a lot of difference in performance and in removing bottlenecks before final execution. But for these additional parameters are needed to consider. Therefore, in this research work parameters like inter node bandwidth, traffic, congestion have been used for building a plan for scheduling, simulated results show significant improvements in performance is concerning of time performance parameters.