@inproceedings{09123a3dac1e4db89fecccb2ffcee227,
title = "An adaptive routing based on an improved ant colony optimization in LEO satellite networks",
abstract = "Ant colony optimization (ACO) has been proposed as a promising algorithm for adaptive routing in communication networks. The algorithm is being successfully applied to optimization problems in a variety of fields. The original ACO has the disadvantages of stagnation behavior and slow convergence .The paper testes and improves the variants of the original ACO in order to give better performances. The improved routing algorithm is simulated in Iridium satellite constellation. The results show that the improved ACO not only achieves fast convergence in dynamic topology networks, but also can avoid networks congestion and counterpoise the load of the network.",
keywords = "ACO, Adaptive routing, LEO, Mobile agents",
author = "Gao, \{Zi He\} and Qing Guo and Ping Wang",
year = "2007",
doi = "10.1109/ICMLC.2007.4370296",
language = "英语",
isbn = "142440973X",
series = "Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007",
pages = "1041--1044",
booktitle = "Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007",
note = "6th International Conference on Machine Learning and Cybernetics, ICMLC 2007 ; Conference date: 19-08-2007 Through 22-08-2007",
}