An efficient tasks scheduling algorithm for batch processing heterogeneous cloud environment. (29th August 2022)

• Record Type: Journal Article
• Authors: Shukla, Dhirendra Kumar; Kumar, Divya; Kushwaha, Dharmender Singh
• Is Part Of: International journal of advanced intelligence paradigms. Volume 23:Number 1/2(2022)
• Page Start: 203
• Page End: 216
• Publication Date: 2022-08-29
• Subjects: makespan -- average node utilisation -- task scheduling -- cloud computing; Artificial intelligence -- Periodicals; Machine theory -- Periodicals; Fuzzy logic -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-0386

Abstract

The recent advancements in virtualisation technology have led to the exponential growth of cloud computing. The capability to provide services in the various communities such as research, business, etc. has accounted for its growing popularity. The tasks requested by various clients are allocated to the available resources. Makespan is the total time taken to process a set of tasks for its complete execution. The makespan reduction is the main objective of the scheduling in clouds. This paper proposes an approach for efficient scheduling of the tasks to the heterogeneous cloud data centre in order to minimise the makespan. The proposed approach achieves multiple objectives such as minimisation of overall makespan and maximisation of CPU utilisation. The proposed algorithm is tested on the benchmark dataset. Experiments reveal that the proposed algorithm reduces the overall makespan up to 24.69% as compared to other existing algorithms. Also, average resource utilisation increases up to 4.29%.