Abstract
We study in simulation the performance of two MANET routing algorithms in an urban environment. The two algorithms, AODV and AntHocNet, are representative of two different approaches and design methodologies. AODV is a state-of-the-art algorithm following a purely reactive approach. AntHocNet is based on Ant Colony Optimization and integrates proactive and reactive mechanisms. We investigate the usefulness of the different approaches they adopt when confronted with the peculiarities of urban environments and real-world applications. At this aim we define a detailed and realistic simulation setup in terms of radio propagation, constrained node mobility, and data traffic.
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References
Tschudin, C., Gunningberg, P., Lundgren, H., Nordström, E.: Lessons from experimental MANET research. Ad Hoc Networks Journal 3(2), 221–233 (2005)
Huang, E., Hu, W., Crowcroft, J., Wassell, I.: Towards commercial mobile ad hoc network applications: A radio dispatch system. In: Proceedings of the sixth ACM Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc) (2005)
Liu, J., Yuan, Y., Nicol, D., Gray, R., Newport, C., Kotz, D., Perrone, L.: Empirical validation of wireless models in simulations of ad hoc routing protocols. Simulation 81(4), 307–323 (2005)
Ducatelle, F., Di Caro, G., Gambardella, L.M.: A study on the use of MANETs in urban environments. Technical Report 01-07, IDSIA (2007)
Di Caro, G.A., Ducatelle, F., Gambardella, L.: AntHocNet: an adaptive nature-inspired algorithm for routing in mobile ad hoc networks. European Transactions on Telecommunications (ETT) 16(5) (2005)
Ducatelle, F., Di Caro, G.A., Gambardella, L.: Using ant agents to combine reactive and proactive strategies for routing in mobile ad hoc networks. International Journal of Computational Intelligence and Applications (IJCIA) 5(2) (2005)
Perkins, C., Royer, E.: Ad-hoc on-demand distance vector routing. In: Proceedings of the 2nd IEEE Workshop on Mobile Computing Sys. and Applications (1999)
Dorigo, M., Di Caro, G.A., Gambardella, L.M.: Ant algorithms for distributed discrete optimization. Artificial Life 5(2), 137–172 (1999)
Clausen, T., Jacquet, P., Laouiti, A., Muhlethaler, P., Qayyum, A., Viennot, L.: Optimized link state routing protocol. In: Proceedings of IEEE INMIC (2001)
Rajagopalan, S., Shen, C.: ANSI: A swarm intelligence-based unicast routing protocol for hybrid ad hoc networks. Journal of Systems Architecture 52(8-9) (2006)
Goldsmith, A.: Wireless Communications. Cambridge University Press, Cambridge (2005)
Sridhara, V., Kim, J., Bohacek, S.: Performance of urban mesh networks. In: Proceedings of ACM MSWiM (2005)
Schmitz, A., Wenig, M.: The effect of the radio wave propagation model in mobile ad hoc networks. In: Proceedings of ACM MSWiM (2006)
Scalable Network Technologies, Inc.: QualNet Simulator, Version 3.8 (2005), http://www.scalable-networks.com
Gerla, M., Tang, K., Bagrodia, R.: TCP performance in wireless multihop networks. In: 2nd IEEE Workshop on Mobile Computing Sys. and Applications (1999)
Johnson, D., Maltz, D.: Dynamic Source Routing in Ad Hoc Wireless Networks. In: Mobile Computing. Kluwer Academic Publishers, Dordrecht (1996)
Marinoni, S., Kari, H.H.: Ad hoc routing protocol performance in a realistic environment. In: Proceedings of IEEE ICN (2006)
Sridhara, V., Bohacek, S.: Realistic propagation simulation of urban mesh networks. Computer Networks 51(12), 3392–3412 (2007)
AWE Communications: WinProp software suite
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Di Caro, G.A., Ducatelle, F., Gambardella, L.M. (2008). A Simulation Study of Routing Performance in Realistic Urban Scenarios for MANETs. In: Dorigo, M., Birattari, M., Blum, C., Clerc, M., Stützle, T., Winfield, A.F.T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2008. Lecture Notes in Computer Science, vol 5217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87527-7_19
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DOI: https://doi.org/10.1007/978-3-540-87527-7_19
Publisher Name: Springer, Berlin, Heidelberg
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