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Ant Colony Optimization for Channel Assignment Problem in a Clustered Mobile Ad Hoc Network

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Advances in Swarm Intelligence (ICSI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7928))

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Abstract

This paper presents an ant colony optimization (ACO) method as a method for channel assignment in a mobile ad hoc network (MANET), where achieving high spectral efficiency necessitates an efficient channel assignment. The suggested algorithm is intended for graph-coloring problems and it is specifically tweaked to the channel assignment problem in MANET with a clustered network topology. A multi-objective function is designed to make a tradeoff between maximizing spectral utilization and minimizing interference. We compare the convergence behavior and performance of ACO-based method with obtained results from a grouping genetic algorithm (GGA).

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Author information

Authors and Affiliations

  1. School of Information Science, Computer and Electrical Engineering, Halmstad University, Sweden

    Mahboobeh Parsapoor & Urban Bilstrup

Authors
  1. Mahboobeh Parsapoor
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  2. Urban Bilstrup
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), School of lectronics Engineering and Computer Science, Department of Machine Intelligence, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, 215123, Suzhou, China

    Yuhui Shi

  3. Automation College, Harbin Engineering University, 150001, Harbin, China

    Hongwei Mo

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© 2013 Springer-Verlag Berlin Heidelberg

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Parsapoor, M., Bilstrup, U. (2013). Ant Colony Optimization for Channel Assignment Problem in a Clustered Mobile Ad Hoc Network. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38703-6_37

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  • DOI: https://doi.org/10.1007/978-3-642-38703-6_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38702-9

  • Online ISBN: 978-3-642-38703-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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