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Evolving Proactive Aggregation Protocols

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4971))

Abstract

We present an approach for the automated synthesis of proactive aggregation protocols using Genetic Programming and discuss major decisions in modeling and simulating distributed aggregation protocols. We develop a genotype, which is an abstract specification form for aggregation protocols. Finally we show the evolution of a distributed average protocol under various conditions to demonstrate the utility of our approach.

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References

  1. Weise, T., Geihs, K.: Genetic programming techniques for sensor networks. In: 5. GI/ITG KuVS Fachgespräch “Drahtlose Sensornetze”, Stuttgart, Germany, pp. 21–25 (2006)

    Google Scholar 

  2. Weise, T., Geihs, K.: Dgpf – an adaptable framework for distributed multi-objective search algorithms applied to the genetic programming of sensor networks. In: 2nd International Conference on Bioinspired Optimization Methods and their Application, BIOMA 2006, pp. 157–166. Ljubljana, Slovenia (2006)

    Google Scholar 

  3. Weise, T., Geihs, K., Baer, P.A.: Genetic Programming for Proactive Aggregation Protocols. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds.) ICANNGA 2007. LNCS, vol. 4431, pp. 167–173. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  4. van Renesse, R.: The Importance of Aggregation. In: Schiper, A., Shvartsman, M.M.A.A., Weatherspoon, H., Zhao, B.Y. (eds.) Future Directions in Distributed Computing. LNCS, vol. 2584, pp. 87–92. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  5. Chong, C.-Y., Kumar, S.P.: Sensor networks: evolution, opportunities, and challenges. Proceedings of the IEEE 91(8), 1247–1256 (2003)

    Google Scholar 

  6. Jelasity, M., Montresor, A., Babaoglu, O.: Gossip-based aggregation in large dynamic networks. ACM Trans. Comput. Syst. 23(3), 219–252 (2005)

    Article  Google Scholar 

  7. Kempe, D., Dobra, A., Gehrke, J.: Gossip-based computation of aggregate information. In: Proceedings of 44th Symposium on Foundations of Computer Science (FOCS 2003), Cambridge, USA, pp. 482–491. IEEE Computer Society Press, Los Alamitos (2003)

    Chapter  Google Scholar 

  8. Koza, J.R.: Genetic Programming, On the Programming of Computers by Means of Natural Selection. The MIT Press, Cambridge (1992), ISBN: 0262111705

    MATH  Google Scholar 

  9. Nguyen, X.H., et al.: Solving the symbolic regression problem with tree-adjunct grammar guided genetic programming: the comparative results. In: IEEE Congress on Evolutionary Computation, CEC 2002, Honolulu, USA, pp. 1326–1331 (2002)

    Google Scholar 

  10. Lopes, H.S., Weinert, W.R.: EGIPSYS: an enhanced gene expression programming approach for symbolic regression problems. Int. J. of Ap. Math. and Com. Sci. 14 (2004)

    Google Scholar 

  11. Weise, T.: Global Optimization Algorithms – Theory and Application (2007), http://www.it-weise.de/

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Michael O’Neill Leonardo Vanneschi Steven Gustafson Anna Isabel Esparcia Alcázar Ivanoe De Falco Antonio Della Cioppa Ernesto Tarantino

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© 2008 Springer-Verlag Berlin Heidelberg

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Weise, T., Zapf, M., Geihs, K. (2008). Evolving Proactive Aggregation Protocols. In: O’Neill, M., et al. Genetic Programming. EuroGP 2008. Lecture Notes in Computer Science, vol 4971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78671-9_22

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  • DOI: https://doi.org/10.1007/978-3-540-78671-9_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78670-2

  • Online ISBN: 978-3-540-78671-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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