Task scheduling in cloud environment: optimization, security prioritization and processor selection schemes

Abstract Cloud computing is an extremely important infrastructure used to perform tasks over processing units. Despite its numerous benefits, a cloud platform has several challenges preventing it from carrying out efficient workflow submission. One of these linked task scheduling. An optimization problem related this the maximal determination scheduling criteria. Existing methods have been unable find quality service (QoS) limits users- like meeting economic restrictions and reduction makespan. Of all methods, Heterogeneous Earliest Finish Time (HEFT) algorithm produces maximum outcomes for in heterogeneous environment reduced time. Reviewed literature proves that HEFT terms execution time schedule. The makes use average communication computation costs as weights DAG. In some cases, however, cost selecting first empty slot may not be enough good solution produced. paper, we propose different versions altered produce improved results. stage (rank generation), execute methodologies calculate ranks, second stage, alter how slots are selected These alterations do add any primary algorithm, reduce makespan virtual machines’ submissions. Our findings suggest better performance than basic regarding decreased schedule length problems.