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A Novel Hybrid Clustering Based Transmission Protocol for Wireless Body Area Networks

Neelam Sharma1,*, Harshita Chadha2, Karan Singh3, B. M. Singh4, Nitish Pathak5

1 Research Scholar, Computer Science and Engineering, Uttarakhand Technical University (UTU), Dehradun, India
2 Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, India
3 School of Computer & Systems Sciences, Jawaharlal Nehru University (JNU), Delhi, India
4 College of Engineering Roorkee, UTU, Dehradun, India
5 Department of Information Technology, KIET Group of Institutions, Ghaziabad, India

* Corresponding Author: Neelam Sharma. Email: email

(This article belongs to this Special Issue: Intelligent Communication Systems: Smart Wireless Digital Devices and IoT)

Computers, Materials & Continua 2021, 69(2), 2459-2473.


Wireless sensor networks are a collection of intelligent sensor devices that are connected to one another and have the capability to exchange information packets amongst themselves. In recent years, this field of research has become increasingly popular due to the host of useful applications it can potentially serve. A deep analysis of the concepts associated with this domain reveals that the two main problems that are to be tackled here are throughput enhancement and network security improvement. The present article takes on one of these two issues namely the throughput enhancement. For the purpose of improving network productivity, a hybrid clustering based packet propagation protocol has been proposed. The protocol makes use of not only clustering mechanisms of machine learning but also utilizes the traditional forwarding function approach to arrive at an optimum model. The result of the simulation is a novel transmission protocol which significantly enhances network productivity and increases throughput value.


Cite This Article

N. Sharma, H. Chadha, K. Singh, B. M. Singh and N. Pathak, "A novel hybrid clustering based transmission protocol for wireless body area networks," Computers, Materials & Continua, vol. 69, no.2, pp. 2459–2473, 2021.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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