Lokesh Sivanandam, Sakthivel Periyasamy and Uma Maheswari Oorkavalan
Time Optimization in Cloud Computing with the Heterogeneous Earliest Finish Time Algorithm
Dynamic Systems and Applications 30 (2021) No. 10, 1653 – 1668

https://doi.org/10.46719/dsa202130.10.08

ABSTRACT.
One of the most widely used platforms for executing works as processing elements via virtual machines is cloud computing. However, in order to use workflow apps effectively, a number of challenges must be solved. One of the most important issues in cloud computing is time optimization. The best scheduling of cloud computing works is an NP optimization problem for which several techniques have been presented. The Heterogeneous Early Finish Time (HEFT) technique is proposed in this paper to achieve time optimization across virtual machines, while attempting to reduce the completion time of a specific workflow application under a user-specified financial limit. To test its performance, the proposed optimization technique is compared with existing timing algorithms with respect to time optimization and performance. The task completion and runtime of the proposed algorithm is reduced, when compared to the existing algorithms.

Keywords: Cloud Computing, Time optimization, Heterogeneous Earliest Finish Time (HEFT), Task Scheduling