A fuzzy-based method for task scheduling in the cloud environments using inverted ant colony optimisation algorithm Online publication date: Mon, 19-Aug-2019
by Poopak Azad; Nima Jafari Navimipour; Mehdi Hosseinzadeh
International Journal of Bio-Inspired Computation (IJBIC), Vol. 14, No. 2, 2019
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.
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