New Heuristic Function in Ant Colony System for Job Scheduling in Grid Computing

Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem. Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms. Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve differenttypes of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges. Thispaper focuses on enhancing the heuristicfunction where information about recent ants’ discoveries will be taken into account. Experiments were conducted using a simulator with dynamic environment features to mimicthe grid environment.Results show that the proposed enhanced algorithm produce better output in term of utilization and makespan. Key-Words: -Ant colony optimization, ant colony system, heuristic function, job scheduling, grid computing.