Balanced Job Scheduling Based on Ant Algorithm for Grid Network

Abstract

Job scheduling in grid computing is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign jobs to resources in grids. The main scope of this article is to propose a new Ant Colony Optimization (ACO) algorithm for balanced job scheduling in the Grid environment. To achieve the above goal, we will indicate a way to balance the entire system load while minimizing the makespan of a given set of jobs. Based on the experimental results, the proposed algorithm confidently demonstrates its practicability and competitiveness compared with other job scheduling algorithms.

The Smallest “Miner” of the Animal Kingdom and Its Importance for Raw Materials Exploitation

“…Humans have exploited the ant's example in many phases of mine design; from mining and transporting material to the development of algorithms that mimic how to select optimal routes to the food source [13][14][15][16][17]. Ants can also help humans after the end of their lives, by providing storage space that humans can use to store not food, but energy [18,19].…”