An ACO Inspired Strategy to Improve Jobs Scheduling in a Grid Environment

Authors:
Marilena Bandieramonte;Antonella Stefano;Giovanni Morana
Affiliations:
Dept. of Computer Science and Telecommunication engineering, Catania University, Italy;Dept. of Computer Science and Telecommunication engineering, Catania University, Italy;Dept. of Computer Science and Telecommunication engineering, Catania University, Italy
Venue:
ICA3PP '08 Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing
Year:
2008

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Abstract

Scheduling is one of the most crucial issue in a grid environment because it strongly affects the performance of the whole system. In literature there are several algorithms that try to obtain the best performance possible for the specified requirements; taking into account that the issue of allocating jobs on resources is a combinatorial optimization problem, NP-hard in most cases, several heuristics have been proposed to provide good performance. In this work an algorithm inspired to Ant Colony Optimization theory is proposed: this algorithm, named Aliened Ant Algorithm, is based on a different interpretation of pheromone trails.The goodness of the proposed algorithm, in term of load balancing and average queue waiting time, has been evaluated by mean of a vast campaign of simulations carried out on some real scenarios of a grid infrastructure.