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Dynamic Routing Exponent Strategies for Ant-Based Protocols

  • Conference paper
Applications of Evolutionary Computation (EvoApplications 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6625))

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Abstract

In ant-based routing protocols, the routing exponent controls how ants hop from node to node to discover routes based on pheromone values. It has been shown that stable multi-route solutions for small routing exponent values are dynamically connected to stable single-route solutions for large routing exponent values. These stable single-route solutions correspond to paths that have the smallest hop count. In this paper, we leverage this idea to improve the performance of ant-based routing protocols by dynamically adjusting the routing exponent. The results are validated via simulation.

This work is supported by U.S. Army Research Laboratory contract #W911QX-09-C-0076. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Army Research Laboratory or the U.S. Government.

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Author information

Authors and Affiliations

  1. Mathematical Sciences, University of Delaware, Newark, DE, 19716, USA

    Rui Fang & Louis F. Rossi

  2. Computer and Information Sciences, University of Delaware, Newark, DE, 19716, USA

    Zequn Huang & Chien-Chung Shen

Authors
  1. Rui Fang
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  2. Zequn Huang
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  3. Louis F. Rossi
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  4. Chien-Chung Shen
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, University of Strathclyde, 16 Richmond Street, G1 1XQ, Glasgow, UK

    Cecilia Di Chio

  2. School of Business, University College Dublin, 4, Belfield, Dublin, UK

    Anthony Brabazon

  3. Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Galleria 2, 6928, Manno-Lugano, Switzerland

    Gianni A. Di Caro

  4. Institute of Computer Science, University of Bremen, 28359, Bremen, Germany

    Rolf Drechsler

  5. Next Generation Intelligent Networks Research Center (nexGIN RC), National University of Computer & Emerging Sciences (FAST-NU), Islamabad, Pakistan

    Muddassar Farooq

  6. Department of Information Systems, Johannes Gutenberg-Universität, 55099, Mainz, Germany

    Jörn Grahl

  7. Mathematics and Computer Science Depatment, University of Richmond, 23173, Richmond, VA, USA

    Gary Greenfield

  8. ICD - OSI, University of Technology of Troyes, 12, Rue Marie Curie, BP 2060, 10010, Troyes, France

    Christian Prins

  9. Facultad de Informatica, Universidade de A Coruña, 15071, Coruña, CP, Spain

    Juan Romero

  10. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

  11. Consiglio Nazionale delle Ricerche (CNR), Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), Via P. Castellino 111, 80131, Naples, Italy

    Ernesto Tarantino

  12. Dipartimento di Tecnologie dell’Informazione, Università degli Studi di Milano, Via Bramante 65, 26013, Crema (CR), Italy

    Andrea G. B. Tettamanzi

  13. School of Computing, Edinburgh Napier University, 10 Clinton Road, EH10 5DT, Edinburgh, UK

    Neil Urquhart

  14. Computer Engineering Department, Istanbul Technical University, Room Nr. 3302, Maslak, 34469, Istanbul, Turkey

    A. Åžima Uyar

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© 2011 Springer-Verlag Berlin Heidelberg

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Fang, R., Huang, Z., Rossi, L.F., Shen, CC. (2011). Dynamic Routing Exponent Strategies for Ant-Based Protocols. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2011. Lecture Notes in Computer Science, vol 6625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20520-0_3

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  • DOI: https://doi.org/10.1007/978-3-642-20520-0_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20519-4

  • Online ISBN: 978-3-642-20520-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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