Ant-based load balancing in telecommunications networks
Adaptive Behavior
Optical burst switching (OBS) - a new paradigm for an optical Internet
Journal of High Speed Networks - Special issue on optical networking
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Optical networks: a practical perspective
Optical networks: a practical perspective
Ant Colony Optimization
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
IEEE Computational Intelligence Magazine
Ant colony optimization for routing and load-balancing: survey and new directions
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Optical burst switching: a new area in optical networking research
IEEE Network: The Magazine of Global Internetworking
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This work proposes a distributed framework for routing path optimization in Optical Burst-Switched (OBS) networks loosely mimicking the foraging behavior of ants, which in the past has originated the Ant Colony Optimization (ACO) metaheuristic. The distributed framework consists of additional data structures stored at the nodes and special control packets used to estimate the goodness of the routing paths and update the routing tables of the nodes. The performance of the ACO-based framework is evaluated, through network simulation, using two reference network topologies and compared with that obtained with shortest path routing and centralized routing path optimization. The simulation results show that the distributed framework significantly improves the performance of OBS networks, when compared to that of using shortest path routing, and attains a comparable performance to that of the centralized strategy. Moreover, the results also suggest that the framework is robust, as it does not require fine tuning its main parameters.