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Analysis of Emergent Behavior for GA-based Topology Control Mechanism for Self-Spreading Nodes in MANETs

  • Chapter
Advances in Intelligent Modelling and Simulation

Part of the book series: Studies in Computational Intelligence ((SCI,volume 422))

Abstract

We introduce a genetic algorithm based MANET topology control mechanism to be used in decision making process of adaptive and autonomic systems at run time. A mobile node adapts its speed and direction using limited information collected from local neighbors operating in an unknown geographical terrain. We represent the genetic operators (i.e., selection, crossover and mutation) as a dynamical system model to describe the behavior of a single node’s decision mechanism. In this dynamical system model each mobile node is viewed as a stochastic variable. We build a homogeneous Markov chain to study the convergent nature of multiple mobile nodes running our algorithm, called FGA. Each state in our chain represents a configuration of the nodes in a MANET for a given instant. The homogeneous Markov chain model of our FGA is shown to be ergodic; its convergence is demonstrated using Dobrushin’s contraction coefficients. We also observe that the nodes with longer communication ranges utilize more information about their neighborhood to make better decisions, require less movement and converge faster, whereas smaller communication ranges utilize limited information, take more time to escape local optima, and, hence, consume more energy.

This research was initiated with support from collaborative participation in the Communications Networks Consortium sponsored by the U.S. Army Research Lab under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011, the National Science Foundation grants ECS-0421159 and CNS-0619577 and US Army, Fort Monmouth, New Jersey, Army Communications-Electronics RD&E Center Grant W15P7T-09-CS021.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, The City College of New York, NY, 10031, New York, USA

    Stephen Gundry, Jianmin Zou & M. Umit Uyar

  2. Lehman College of the City University of New York, Bronx, NY, 10468, USA

    Elkin Urrea

  3. BAE Systems - AIT, Burlington, MA, 01803, USA

    Cem Safak Sahin

  4. The Graduate Center of the City University of New York, New York, NY, 10016, USA

    Janusz Kusyk & M. Umit Uyar

Authors
  1. Stephen Gundry
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  2. Jianmin Zou
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  3. Elkin Urrea
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  4. Cem Safak Sahin
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  5. Janusz Kusyk
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  6. M. Umit Uyar
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Corresponding author

Correspondence to Stephen Gundry .

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Editors and Affiliations

  1. Institute of Computer Science, Cracow University of Technology, ul. Warszawska 24, Cracow, 31-155, Poland

    Joanna Kołodziej

  2. , Department of Electrical and Computer, North Dakota State University, Fargo, 58108-6050, USA

    Samee Ullah Khan

  3. Department of Computer Science, Cracow University of Technology, ul. Warszawska 24, Cracow, 31-155, Poland

    Tadeusz Burczy´nski

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Gundry, S., Zou, J., Urrea, E., Sahin, C.S., Kusyk, J., Uyar, M.U. (2012). Analysis of Emergent Behavior for GA-based Topology Control Mechanism for Self-Spreading Nodes in MANETs. In: Kołodziej, J., Khan, S., Burczy´nski, T. (eds) Advances in Intelligent Modelling and Simulation. Studies in Computational Intelligence, vol 422. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30154-4_8

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  • DOI: https://doi.org/10.1007/978-3-642-30154-4_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30153-7

  • Online ISBN: 978-3-642-30154-4

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