Application of ant colony optimization to adaptive routing in aleo telecomunications satellite network

Ant colony optimization (Aco) has been proposed as a promising tool for adaptive routing in telecommunications networks. The algorithm is applied here to a simulation of a satellite telecommunications network with 72Leo nodes and 121 earth stations. Three variants ofAco are tested in order to assess the relative importance of the different components of the algorithm. The bestAco variant consistently gives performance superior to that obtained with a standard link state algorithm (Spf), under a variety of traffic conditions, and at negligible cost in terms of routing bandwidth.RésuméUne méthode d’optimisation utilisant des agents de type“fourmis”(ant colony optimi zation) est proposée pour les problèmes de routage dynamique dans les réseaux de télécommunications. L’algorithme est appliqué à un réseau de satellites comprenant 72 satellites leo et 121 stations terriennes. Trois versions de Valgorithme sont comparées dans le but d’évaluer l’importance relative des différentes composantes de l’algorithme. La version complète de l’algorithme donne de façon systématique des résultats meilleurs que ceux obtenus par Valgorithme standard spf, ceci pour différentes conditions de trafic, et un coût moindre en termes de bande passante.

[1]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[2]  Luca Maria Gambardella,et al.  Ant Algorithms for Discrete Optimization , 1999, Artificial Life.

[3]  Alain Hertz,et al.  Ants can colour graphs , 1997 .

[4]  Guy Theraulaz,et al.  Routing in Telecommunications Networks with Ant-Like Agents , 1999, IATA.

[5]  Vittorio Maniezzo,et al.  The Ant System Applied to the Quadratic Assignment Problem , 1999, IEEE Trans. Knowl. Data Eng..

[6]  Gianni A. Di Caro,et al.  AntNet: A Mobile Agents Approach to Adaptive Routing , 1999 .

[7]  Marco Dorigo,et al.  Mobile agents for adaptive routing , 1998, Proceedings of the Thirty-First Hawaii International Conference on System Sciences.

[8]  Marco Dorigo,et al.  AntNet: Distributed Stigmergetic Control for Communications Networks , 1998, J. Artif. Intell. Res..

[9]  M Dorigo,et al.  Ant colonies for the quadratic assignment problem , 1999, J. Oper. Res. Soc..

[10]  Giovanni Righini,et al.  Heuristics from Nature for Hard Combinatorial Optimization Problems , 1996 .

[11]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[12]  Martin Heusse,et al.  Adaptive Agent-Driven Routing and Load Balancing in Communication Networks , 1998, Adv. Complex Syst..

[13]  M. Werner,et al.  Traffic Flows and Dynamic Routing in LEO Intersatellite Link Networks. , 1997 .

[14]  Janet Bruten,et al.  Ant-like agents for load balancing in telecommunications networks , 1997, AGENTS '97.