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Optimized clustering in vehicular ad hoc networks based on honey bee and genetic algorithm for internet of things

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Abstract

In vehicular ad hoc network (VANET), the size of routing table can be reduced with the help of clustering architecture. The frequent changes in topology are the noteworthy characteristics of a VANET as its nature is dynamic. To manage the topology dynamics in VANET with less overhead, the concept of clustering can be used. Henceforth, an effective procedure that adjusts quickly to the topology changes should be designed. Firstly, the clustering problem (CP) in VANET is formulated into a dynamic optimization problem in this paper. Secondly, an optimization algorithm named Vehicular Genetic Bee Clustering (VGBC) based on honey bee algorithm and properties of genetic algorithm solves the CP in VANETs is suggested. In VGBC, individuals (bees) represent a realistic clustering structure and its fitness is measured on the basis of load balancing and stability. A technique that merges the properties of genetic algorithm and honey bee algorithm is proposed. It helps the population to handle the topology changes and harvest high quality solutions. The simulation results piloted for justification demonstrate that the VGBC form steady and balanced clusters. The simulation results are matched with state of the art clustering schemes in VANET. The VGBC outperform existing schemes in terms of cluster count, cluster duration, re-affiliation rate, computational overhead, load balancing, VANET lifetime and clustering overhead.

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Acknowledgements

The research is supported by Higher Education Commission Islamabad.

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Authors and Affiliations

  1. Department of Computer Science, Abdul Wali Khan University Mardan, Mardan, Pakistan

    Masood Ahmad & Ishtiaq Wahid

  2. Department of Electrical Engineering, National University of Computer and Emerging Sciences, Islamabad, Pakistan

    Ataul Aziz Ikram

  3. Department of Computer Science & IT, Sarhad University of Science and Technology, Peshawar, Pakistan

    Fasee Ullah

  4. Department of Computer Engineering, Bahria University, Islamabad, Pakistan

    Awais Ahmad

  5. Institute of Management Sciences, Peshawar, Pakistan

    Fakhri Alam Khan

Authors
  1. Masood Ahmad
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  2. Ataul Aziz Ikram
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  4. Fasee Ullah
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  5. Awais Ahmad
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Correspondence to Fasee Ullah.

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This article is part of the Topical Collection: Special Issue on IoT System Technologies based on Quality of Experience Guest Editors: Cho Jaeik, Naveen Chilamkurti, and SJ Wang

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Ahmad, M., Ikram, A.A., Wahid, I. et al. Optimized clustering in vehicular ad hoc networks based on honey bee and genetic algorithm for internet of things. Peer-to-Peer Netw. Appl. 13, 532–547 (2020). https://doi.org/10.1007/s12083-019-00724-4

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  • DOI: https://doi.org/10.1007/s12083-019-00724-4

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