Abstract
Mobile ad hoc networks are a class of highly dynamic networks. In previous work, we developed a new routing algorithm, called AntHocNet, for these challenging network environments. AntHocNet has been designed after the Ant Colony Optimization (ACO) framework, and its general architecture shares strong similarities with the architectures of typical ACO implementations for network routing. On the other hand, AntHocNet also contains several elements which are new to ACO routing implementations, such as the combination of ant-based path sampling with a lightweight information bootstrapping process, the use of both reactive and proactive components, and the use of composite pheromone metrics. In this paper we discuss all these elements, pointing out their general usefulness to face the multiple challenges of mobile ad hoc networks, and perform an evaluation of their working and effect on performance through extensive simulation studies.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Royer, E., Toh, C.K.: A review of current routing protocols for ad hoc mobile wireless networks. IEEE Personal Communications (1999)
Di Caro, G., Ducatelle, F., Gambardella, L.: AntHocNet: an adaptive nature-inspired algorithm for routing in mobile ad hoc networks. European Transactions on Telecommunications, Special Issue on Self Organization in Mobile Networking 16(5), 443–455 (2005)
Ducatelle, F., Di Caro, G., Gambardella, L.: Using ant agents to combine reactive and proactive strategies for routing in mobile ad hoc networks. Int. Journal of Computational Intelligence and Applications (IJCIA), Special Issue on Nature-Inspired Approaches to Networks and Telecommunications 5(2), 169–184 (2005)
Di Caro, G., Ducatelle, F., Gambardella, L.: Swarm intelligence for routing in mobile ad hoc networks. In: Proceedings of the 2005 IEEE Swarm Intelligence Symposium (SIS) (2005)
Ducatelle, F., Di Caro, G., Gambardella, L.: Ant agents for hybrid multipath routing in mobile ad hoc networks. In: Proceedings of the Second Annual Conference on Wireless On demand Network Systems and Services (WONS), St. Moritz, Switzerland (2005)
Di Caro, G., Ducatelle, F., Gambardella, L.: AntHocNet: an ant-based hybrid routing algorithm for mobile ad hoc networks. In: Yao, X., Burke, E.K., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J.E., Tiňo, P., Kabán, A., Schwefel, H.-P. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 461–470. Springer, Heidelberg (2004)
Di Caro, G.: Ant Colony Optimization and its application to adaptive routing in telecommunication networks. PhD thesis, Faculté des Sciences Appliquées, Université Libre de Bruxelles, Brussels, Belgium (2004)
Sutton, R., Barto, A.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)
Di Caro, G., Dorigo, M.: AntNet: Distributed stigmergetic control for communications networks. J. of Artificial Intelligence Research (JAIR) 9, 317–365 (1998)
Shen, C.C., Jaikaeo, C., Srisathapornphat, C., Huang, Z., Rajagopalan, S.: Ad hoc networking with swarm intelligence. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds.) ANTS 2004. LNCS, vol. 3172, Springer, Heidelberg (2004)
Baras, J.S., Mehta, H.: A probabilistic emergent routing algorithm for mobile ad hoc networks. In: WiOpt 2003: Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (2003)
Günes, M., Kähmer, M., Bouazizi, I.: Ant-routing-algorithm (ARA) for mobile multi-hop ad-hoc networks - new features and results. In: Proceedings of the 2nd Mediterranean Workshop on Ad-Hoc Networks (Med-Hoc-Net 2003), Mahdia, Tunisia (2003)
Di Caro, G., Ducatelle, F., Gambardella, L.: Studies of routing performance in a city-like testbed for mobile ad hoc networks. Technical Report 07-06, IDSIA, Lugano (Switzerland) (2006)
Perkins, C., Royer, E.: Ad-hoc on-demand distance vector routing. In: Proc. of the 2nd IEEE Workshop on Mobile Computing Systems and Applications (1999)
Clausen, T., Jacquet, P., Laouiti, A., Muhlethaler, P., Qayyum, A., Viennot, L.: Optimized link state routing protocol. In: Proceedings of IEEE INMIC (2001)
Bertsekas, D., Gallager, R.: Data Networks. Prentice Hall, Englewood Cliffs (1992)
Scalable Network Technologies, Inc. Culver City, CA, USA: QualNet Simulator, Version 3.8. (2005), http://www.scalable-networks.com
Johnson, D., Maltz, D.: Dynamic Source Routing in Ad Hoc Wireless Networks. In: Mobile Computing, pp. 153–181. Kluwer, Dordrecht (1996)
Rappaport, T.: Wireless communications, principles and practice. Prentice Hall, Englewood Cliffs (1996)
De Couto, D., Aguayo, D., Chambers, B., Morris, R.: Performance of multihop wireless networks: Shortest path is not enough. In: Proceedings of the First Workshop on Hot Topics in Networks (HotNets-I), ACM SIGCOMM (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ducatelle, F., Di Caro, G.A., Gambardella, L.M. (2006). An Analysis of the Different Components of the AntHocNet Routing Algorithm. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2006. Lecture Notes in Computer Science, vol 4150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839088_4
Download citation
DOI: https://doi.org/10.1007/11839088_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38482-3
Online ISBN: 978-3-540-38483-0
eBook Packages: Computer ScienceComputer Science (R0)