Title: A fuzzy-based method for task scheduling in the cloud environments using inverted ant colony optimisation algorithm

Authors: Poopak Azad; Nima Jafari Navimipour; Mehdi Hosseinzadeh

Addresses: Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran ' Young Researchers and Elite Club, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran ' Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran; Computer Science, University of Human Development, Sulaymaniyah, Iraq

Abstract: Cloud computing is the latest emerging trend of distributed computing, in which distributed resources are delivered based on user's demand. In the cloud environment, computing resources need to be scheduled so that providers make the most use of the resources and users will find the applications they need at the lowest cost. In this paper, an inverted ant colony optimisation (IACO) algorithm has been used to solve the task scheduling problem in the cloud environment with the goal of reducing runtime and increasing load balancing. In the proposed method, pheromone repellent is used instead of pheromone gravity, so the effect of pheromone prevents the wrong choice. In order to observe load balance and the effect of pheromone repulsion, fuzzy logic and weight definition have been used. The results have shown that the proposed algorithm while reducing the total time and cost of execution, could also increase load balance.

Keywords: cloud computing; scheduling; inverted ant colony algorithm; IACO; makespan; load balancing; CloudSim.

DOI: 10.1504/IJBIC.2019.101638

International Journal of Bio-Inspired Computation, 2019 Vol.14 No.2, pp.125 - 137

Accepted: 13 Aug 2018
Published online: 19 Aug 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article