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A memetic optimization algorithm for multi-constrained multicast routing in ad hoc networks

Author

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  • Rahab M Ramadan
  • Safa M Gasser
  • Mohamed S El-Mahallawy
  • Karim Hammad
  • Ahmed M El Bakly

Abstract

A mobile ad hoc network is a conventional self-configuring network where the routing optimization problem—subject to various Quality-of-Service (QoS) constraints—represents a major challenge. Unlike previously proposed solutions, in this paper, we propose a memetic algorithm (MA) employing an adaptive mutation parameter, to solve the multicast routing problem with higher search ability and computational efficiency. The proposed algorithm utilizes an updated scheme, based on statistical analysis, to estimate the best values for all MA parameters and enhance MA performance. The numerical results show that the proposed MA improved the delay and jitter of the network, while reducing computational complexity as compared to existing algorithms.

Suggested Citation

  • Rahab M Ramadan & Safa M Gasser & Mohamed S El-Mahallawy & Karim Hammad & Ahmed M El Bakly, 2018. "A memetic optimization algorithm for multi-constrained multicast routing in ad hoc networks," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
    • Handle: RePEc:plo:pone00:0193142
    DOI: 10.1371/journal.pone.0193142
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    References listed on IDEAS

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    1. Abdulaziz Al-Nahari & Mohd Murtadha Mohamad, 2016. "Receiver-Based Ad Hoc On Demand Multipath Routing Protocol for Mobile Ad Hoc Networks," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-18, June.
    2. Maha Abdelhaq & Raed Alsaqour & Shawkat Abdelhaq, 2015. "Securing Mobile Ad Hoc Networks Using Danger Theory-Based Artificial Immune Algorithm," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-16, May.
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    Cited by:

    1. Hossam M J Mustafa & Masri Ayob & Mohd Zakree Ahmad Nazri & Graham Kendall, 2019. "An improved adaptive memetic differential evolution optimization algorithms for data clustering problems," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-28, May.
    2. Hossam M J Mustafa & Masri Ayob & Dheeb Albashish & Sawsan Abu-Taleb, 2020. "Solving text clustering problem using a memetic differential evolution algorithm," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-18, June.

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