Modified firefly with fuzzy based clustering algorithm for cluster-based networks

 
 
 
  • Abstract
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  • References
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  • Abstract


    Cluster-based network comprises a group of clusters with each cluster contains a collection of nodes. The control structures offer effective utilization of resources while managing large dynamic networks. Cluster based network is mainly used for effective load balancing. Different kinds of cluster-based architectures presented in the study for different usage. In cluster based networks, the choice of cluster heads (CH) in cluster based network is a challenging task. Presently, meta-heuristic algorithms become very popular and employed to select CHs effectively. In this paper, we introduce a modified firefly with fuzzy based clustering algorithm and it operates in two levels: modified firefly algorithm (MFA) for candidate CH selection and fuzzy logic for final CH selection. The traditional FF algorithm in modified by the inclusion of tumbling effect to develop MFA and it uses processing capability as a measure to identify the candidate CHs. Next, five input parameters named as residual energy, neighboring node distance, distance to main server, node centrality and node degree to select the final CHs from candidate CHs. An extensive experimentation takes place to verify the goodness of the MFFCA in terms of different performance measures and the results depicted that the MFFCA outperforms the compared clustering techniques.

     

     

     

  • Keywords


    Fiber Optic Communication; Dictionary Based Coding; Data Compression; Textual Dataset.

  • References


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Article ID: 22843
 
DOI: 10.14419/ijet.v7i4.22843




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