INDIAN JOURNAL OF SCIENCE AND TECHNOLOGY RESEARCH ARTICLE OPEN ACCESS Received: 12-04-2022 Accepted: 17-08-2022 Published: 26-09-2022 Citation: Shrivastava V, Shaikh Y (2022) EBTASIC: An Entropy-Based TOPSIS Algorithm for Task Scheduling in IaaS Clouds. Indian Journal of Science and Technology 15(37): 1850-1858. https://doi.org/ 10.17485/IJST/v15i37.799 * Corresponding author. vivek.shrivastava@iips.edu.in Funding: None Competing Interests: None Copyright: © 2022 Shrivastava & Shaikh. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee) ISSN Print: 0974-6846 Electronic: 0974-5645 EBTASIC: An Entropy-Based TOPSIS Algorithm for Task Scheduling in IaaS Clouds Vivek Shrivastava 1* , Yasmin Shaikh 1 1 International Institute of Professional Studies, Devi Ahilya University, Indore-452001, Madhya Pradesh, India Abstract Objectives: To propose an algorithm to balance resource utilization and revenue generation in the cloud environment. Methods: This study proposes the Entropy-Based TOPSIS algorithm for task scheduling in IaaS Clouds (EBTASIC) to balance resource utilization and revenue generation using the objective-based Entropy Weighting Method (EWM) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Findings/Novelty: Various performance evaluation factors are calculated using EBTASIC and compared with baseline algorithms First Come First Serve (FCFS) and Earliest Deadline First (EDF) algorithms over 12750 lease requests with hard deadlines. The actual response time of EBTASIC is 37.61 percent faster than FCFS and 47.95 percent faster than EDF. Total time spent on lease execution by EBTASIC is reduced by 3.43 percent when compared to FCFS and 3.99 percent when compared to EDF. Turnaround time of EBTASIC is lowered by 21.14 percent when compared to FCFS and 28.81 percent when compared to EDF. EBTASIC throughput is enhanced by 40.80 percent over FCFS and 54.3 percent over EDF. The average response time of EBTASIC is shortened by 9.38 percent compared to FCFS and 14.81 percent compared to EDF. Resource utilization of the proposed algorithm EBTASIC is enhanced by 25.54 percent over FCFS and 6.79 percent over the EDF algorithm. Keywords: Task and VM Scheduling; MCDM Techniques; TOPSIS; Entropy Weighting Method; EBTASIC Algorithm 1 Introduction Resource scheduling can be performed based on many criteria such as earliest deadline first, first come first serve, highest revenue first, shortest time first, minimum cost first, minimum makespan first, highest resource utilization first and so on. Taking into account only one criterion for scheduling will yield better results just for that criterion, but a sense of balance is essential in all parameters. https://www.indjst.org/ 1850