Abstract
An analytical justification is proposed for the design and global routing performance of three pheromone update methods proposed for use in Termite, a swarm intelligent routing algorithm for mobile wireless ad-hoc networks. A simple model is used in order to determine the average amount of pheromone present on a link, as well as some basic aspects of the pheromone dynamics. This includes a tendency towards a one-zero pheromone distribution favoring the better link. The pheromone update methods are investigated with the perspective that link pheromone is more an estimate of link utility than simply a routing heuristic. This allows the routing solution to be rephrased from a biological analogy to a more traditional best-metric routing terminology. A signal estimation perspective is suggested.
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References
M. Roth, S. Wicker, Termite: Emergent Ad-Hoc Networking, The Second Mediterranean Workshop on Ad-Hoc Networks, 2003.
M. Roth, S. Wicker, Performance Evaluation of Pheromone Update Methods in Termite, in preparation.
M. Gunes, M. Kahmer, I. Bouazizi, Ant Routing Algorithm (ARA) for Mobile Multi-Hop Ad-Hoc Networks-New Features and Results, The Second Mediterranean Workshop on Ad-Hoc Networks, 2003.
M. Gunes, U. Sorges, I. Bouazizi, ARA-The Ant-Colony Based Routing Algorithm for MANETs, Proceedings of the ICPP Workshop on Ad Hoc Networks (IWAHN 2002), IEEE Computer Society Press, 2002, 79–85.
M. Heissenbuttel, T. Braun, Ants-Based Routing in Large Scale Mobile Ad-Hoc Networks, Kommunikation in Verteilten Systemen (KiVS), 2003.
D. Subramanian, P. Druschel, J. Chen, Ants and Reinforcement Learning: A Case Study in Routing in Dynamic Networks, Proceedings of the International Joint Conference on Artificial Intelligence, 1997.
G. Di Caro, M. Dorigo, Mobile Agents for Adaptive Routing, Technical Report, IRIDIA/97-12, Universit Libre de Bruxelles, Belgium, 1997.
B. Baran, R. Sosa, A New Approach for AntNet Routing, Proceedings of the Ninth International Conference on Computer Communications and Networks, 2000.
R. Schoonderwoerd, O. Holland, J. Bruten, L. Rothkrantz, Ant-Based Load Balancing In Telecommunications Networks, Adaptive Behavior, 1996.
M. Dorigo, G. Di Caro, L. M. Gambardella, Ant Algorithms for Discrete Optimization, Artificial Life, Vol. 5, No. 2, 1999.
K. M. Sim, W. H. Sun, Ant Colony Optimization for Routing and Load-Balancing: Survey and New Directions, IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, Vol. 33, No. 5, September 2003.
E. Bonabeau, M. Dorigo, G. Theraulaz, Swarm Intelligence: From Natural to Artificial Systems, Oxford University Press, 1999.
M. Resnick, Turtles, Termites, and Traffic Jams: Explorations in Massively Parallel Microworlds, Bradford Books, 1997.
J. Broch, D. A. Maltz, D. B. Johnson, Y. Hu, J. Jetcheva, A Performance Comparison of Multi-Hop Wireless Ad Hoc Network Routing Protocols, Proceedings of the Fourth Annual ACM/IEEE International Conference on Mobile Computing and Networking, 1998.
E. Dijkstra, A note on two problems in connection with graphs, Numerische Mathematik, Vol. 1, 269–271, 1959.
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© 2005 International Federation for Information Processing
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Roth, M., Wicker, S. (2005). Asymptotic Pheromone Behavior in Swarm Intelligent MANETs. In: Belding-Royer, E.M., Al Agha, K., Pujolle, G. (eds) Mobile and Wireless Communication Networks. MWCN 2004. IFIP International Federation for Information Processing, vol 162. Springer, Boston, MA. https://doi.org/10.1007/0-387-23150-1_29
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DOI: https://doi.org/10.1007/0-387-23150-1_29
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