Allocating Modules to Processors in a Distributed System
IEEE Transactions on Software Engineering
Ant-like agents for load balancing in telecommunications networks
AGENTS '97 Proceedings of the first international conference on Autonomous agents
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
The grid
ACO algorithms for the quadratic assignment problem
New ideas in optimization
Future Generation Computer Systems
Journal of Parallel and Distributed Computing
Design of Iterated Local Search Algorithms
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem
INFORMS Journal on Computing
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
D-Ants: savings based ants divide and conquer the vehicle routing problem
Computers and Operations Research
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
Genetic Algorithm Based Scheduler for Computational Grids
HPCS '05 Proceedings of the 19th International Symposium on High Performance Computing Systems and Applications
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
Ant colony optimization theory: a survey
Theoretical Computer Science
Simulated Annealing for Grid Scheduling Problem
JVA '06 Proceedings of the IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing
Ant colony optimization for FOP shop scheduling: a case study on different pheromone representations
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Backfilling Using System-Generated Predictions Rather than User Runtime Estimates
IEEE Transactions on Parallel and Distributed Systems
The State of the Art in Grid Scheduling Systems
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 04
An ant algorithm for balanced job scheduling in grids
Future Generation Computer Systems
An ACO Inspired Strategy to Improve Jobs Scheduling in a Grid Environment
ICA3PP '08 Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
Grid load balancing using intelligent agents
Future Generation Computer Systems
Adaptive grid job scheduling with genetic algorithms
Future Generation Computer Systems
Grid jobs scheduling: The Alienated Ant Algorithm solution
Multiagent and Grid Systems
Job Allocation Strategies with User Run Time Estimates for Online Scheduling in Hierarchical Grids
Journal of Grid Computing
Ant algorithm for grid scheduling problem
LSSC'05 Proceedings of the 5th international conference on Large-Scale Scientific Computing
Modeling user runtime estimates
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant colony optimization for resource-constrained project scheduling
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Ant colony optimization for routing and load-balancing: survey and new directions
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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The scheduling in grids is known to be a NP-hard problem. The distributed deployment of nodes, their heterogeneity and their fluctuations in terms of workload and availability make the design of an effective scheduling algorithm a very complex issue. The scientific literature has proposed several heuristics able to tackle this kind of optimization problem using techniques and strategies inspired by nature. The algorithms belonging to ant colony optimization (ACO) paradigm represent an example of these techniques: each one of these algorithms uses strategies inspired by the self-organization ability of real ants for building effective grid schedulers. In this paper, the authors propose an on line, non-clairvoyant, distributed scheduling solution for multi-broker grid based on the alienated ant algorithm (AAA), a new ACO inspired technique exploiting a "non natural" behavior of ants and an inverse interpretation of pheromone trails. The paper introduces the proposed algorithm, explains the differences with other classical ACO approaches, and compares AAA with two different algorithms. The results of simulations show that the AAA guarantees good performance in terms of makespan, average queue waiting time and load balancing capability.