Improving The Performance Of An Advanced Algorithm For Taskflow Scheduling In Cloud Computing

Abstract

The domain of cloud computing with an emphasis on taskflow scheduling optimisation. It emphasises the benefits that cloud resources provide for the both business and research endeavours. The study revolves around these scheduling algorithms, especially the Max-Min algorithm and its improved version, which are essential for optimising resource use and reducing work runtime. It can minimize the makespan, throughput, average waiting time and average response time of workflow executions. These methods optimise resource allocation and improve overall performance by dynamically allocating jobs based the on current workload requirements and real-time data. The algorithm is tested out using CloudSim, the results shown that the Improved Max-Min algorithm has achieved better in almost of the cases considered. Smart scheduling methods can make a big difference in how well cloud resources are used. This leads to cloud networks that are more efficient and can handle the ever-changing needs of today's IT systems. The Improved Max-Min algorithm's ability to prioritize important tasks and change how resources are allocated can make the system run much better and improve its performance. This research adds to our understanding of how to make the most of cloud resources. Studies show that the Improved Max-Min algorithm works well. This study shows how important it is to use advanced scheduling algorithms in cloud computing. These algorithms help use cloud resources better and improve taskflow management.