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Probabilistic neural network based efficient bandwidth allocation in wireless sensor networks

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Abstract

In Wireless Sensor Networks the efficient use of resources is the basic challenge. One such significant challenge is the utilization of bandwidth. The bandwidth is the fundamental resource for transmitting data in a network. The bandwidth must be maximum while gathering and forwarding from the sensor nodes to the Base Station. In this paper, Particle Swarm Optimization algorithm is employed for the formation of successful clustering in wireless sensor network and in choosing the cluster head. Clusters are formed by considering the fitness value of every particle. To reduce the workload of every cluster head, a corresponding cluster assistant node, with maximum fitness value, is selected. Also Probabilistic Neural Network approach is used here for allocating maximum bandwidth for the nodes and for dynamic channel assignment of the nodes. The cluster head which has the global best fitness value will transmit the data to the base station. Experimental results show that the proposed method is better than the conventional methods.

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Acknowledgements

The authors acknowledge the support and encouragement by the Management, Principal and Head of Department of Computer Applications and Electronics and Communication Engineering, towards this work. The authors would like to thank the anonymous reviewers for their insightful comments.

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Authors and Affiliations

  1. Faculty of Computer Applications, MepcoSchlenk Engineering College, Sivakasi, 626005, India

    A. D. C. Navin Dhinnesh

  2. Faculty of Electronics and Communication Engineering, MepcoSchlenk Engineering College, Sivakasi, 626005, India

    T. Sabapathi

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  1. A. D. C. Navin Dhinnesh
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  2. T. Sabapathi
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Correspondence to A. D. C. Navin Dhinnesh.

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Navin Dhinnesh, A.D.C., Sabapathi, T. Probabilistic neural network based efficient bandwidth allocation in wireless sensor networks. J Ambient Intell Human Comput 13, 2001–2012 (2022). https://doi.org/10.1007/s12652-021-02961-z

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