Affiliations: Department of Computers Science and Telecommunication Engineering, Catania University, Italy
Corresponding author: G. Morana, V.le A. Doria 6, 95125 Catania, Italy. Tel.: +39 095 738 2365; Fax: +39 095 738 2397; E-mail: firstname.lastname@example.org
Abstract: Grid is a manifold and highly dynamic scenario. One of the fundamental issues in this environment is related to jobs scheduling; since jobs allocation to resources is a combinatorial optimization problem, NP-hard in most cases, several heuristics have been proposed to achieve near-optimal solutions. This paper proposes a job scheduling policy based on the Alienated Ant Algorithm (AAA), a new metaheuristic strategy freely inspired by the ants' self-organization ability. As it will be shown, AAA is able to find near-optimal solutions adapting its decisions to changing resources states and submitted workload. The experimental results show that the use of the proposed algorithm satisfies expectations.
Keywords: Scheduling algorithms, grid computing, simulation, ant colony optimization, alienated ant algorithm