Abstract
Nature-inspired routing algorithms for fixed networks is an active area of research. In these algorithms, ant- or bee-agents are deployed for collecting the state of a network and providing them to autonomous and fully distributed controllers at each network node. In these routing systems the agents, through local interactions, self-organize to produce system-level behaviors which show adaptivity to changes and perturbations in the network environment. The formal modeling of such fully self-organizing, distributed and adaptive routing systems is a difficult task. In this paper, we propose a scalable formal framework that has following desirable features: (1) it models important performance metrics: throughput, delay and goodness of links, (2) it is scalable to any size of topology, (3) it is robust to changing network traffic conditions. The proposed framework is utilized to model a well-known BeeHive protocol which is further validated on NTTNeT (a 57 node topology). To the best of our knowledge, this is the first formal framework that has been validated on such a large topology.
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References
Bean, N., Costa, A.: An analytic modelling approach for network routing algorithms that use ”ant-like” mobile agents. Computer Networks 49(2), 243–268 (2005)
Di Caro, G., Dorigo, M.: Antnet: Distributed stigmergetic control for communications networks. Journal of Artificial Intelligence Research (JAIR) 9, 317–365 (1998)
Farooq, M.: Bee-inspired Protocol Engineering: from Nature to Networks. Natural Computing Series. Springer, Heidelberg (in press, 2008)
Farooq, M., Di Caro, G.: Routing protocols for next-generation intelligent networks inpired by colective behaviors of insect societies. In: Swarm Intelligence:Introduction and Applications. Natural Computing Series. Springer, Heidelberg (2008)
Kelly, F., Zachary, S., Zeidins, I.: Stochastic Networks Theorey and Applications. Oxford Science Publications (1996)
Taha, H.A.: Operations Research. John Wiley & Sons, Chichester (1982)
Trivedi, K.S.: Probability and Statistics with Reliability, Queuing and Computer Science Applications. John Wiley Interscience Publication, Chichester (2002)
Wedde, H.F., Farooq, M.: A comprehensive review of nature inspired routing algorithms for fixed telecommunication networks. Journal of Systems Architecture 52(8-9), 461–484 (2006)
Wedde, H.F., Farooq, M.: A performance evaluation framework for nature inspired routing algorithms. In: Rothlauf, F., Branke, J., Cagnoni, S., Corne, D.W., Drechsler, R., Jin, Y., Machado, P., Marchiori, E., Romero, J., Smith, G.D., Squillero, G. (eds.) EvoWorkshops 2005. LNCS, vol. 3449, pp. 136–146. Springer, Heidelberg (2005)
Wedde, H.F., Farooq, M., Zhang, Y.: BeeHive: An efficient fault-tolerant routing algorithm inspired by honey bee behavior. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds.) ANTS 2004. LNCS, vol. 3172, pp. 83–94. Springer, Heidelberg (2004)
Zahid, S., Shahzad, M., Ali, S.U., Farooq, M.: A comprehensive formal framework for analyzing the behavior of nature-inspired routing protocols. In: IEEE Congress on Evolutionary Computation, pp. 180–187 (September 2007)
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Shahzad, M., Zahid, S., Farooq, M. (2008). A Scalable Formal Framework for Analyzing the Behavior of Nature-Inspired Routing Protocols. In: Rudolph, G., Jansen, T., Beume, N., Lucas, S., Poloni, C. (eds) Parallel Problem Solving from Nature – PPSN X. PPSN 2008. Lecture Notes in Computer Science, vol 5199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87700-4_112
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DOI: https://doi.org/10.1007/978-3-540-87700-4_112
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