Title: A novel hybrid algorithm for workflow scheduling in cloud

Authors: Isha Agarwal; Swati Gupta; Ravi Shankar Singh

Addresses: Department of Computer Science, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India ' Department of Computer Science, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India ' Department of Computer Science, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India

Abstract: Cloud computing is a service that provides its users all the computing facilities which can be accessed anywhere, at any time through the internet on a pay-per-use basis. There is a huge number of cloud service providers receiving a large number of requests from multiple users around the world, scheduling plays a vital role in assigning those requests to its requested resources. Task scheduling is an NP-hard problem in cloud environments due to which many heuristics and metaheuristics algorithms have been used for obtaining an optimised mapping. In this paper, we designed a hybrid Jaya-particle swarm optimisation (PSO) algorithm. The proposed algorithm combines both the Jaya and PSO to provide us better quality results. Our algorithm is evaluated in terms of execution cost and execution time and achieved better results in comparison with genetic algorithm (GA), PSO, honey bee, cat swarm optimisation (CSO), ant colony optimisation (ACO) and Jaya.

Keywords: task scheduling; cloud computing; workflow scheduling; Jaya; particle swarm optimisation; PSO; execution cost; running time.

DOI: 10.1504/IJCC.2023.134648

International Journal of Cloud Computing, 2023 Vol.12 No.6, pp.605 - 620

Received: 30 Jan 2020
Accepted: 06 Dec 2020
Published online: 03 Nov 2023 *

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