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A Hybrid Approach to Neighbour Discovery in Wireless Sensor Networks

Sagar Mekala1,*, K. Shahu Chatrapati2

1 Department of CSE, Mahatma Gandhi University, 508003, Telangana State, India
2 Department of EEE, JNTUH College of Engineering Manthani, 505212, Telangana State, India

* Corresponding Author: Sagar Mekala. Email:

Intelligent Automation & Soft Computing 2023, 35(1), 581-593.


In the contemporary era of unprecedented innovations such as Internet of Things (IoT), modern applications cannot be imagined without the presence of Wireless Sensor Network (WSN). Nodes in WSN use neighbour discovery (ND) protocols to have necessary communication among the nodes. Neighbour discovery process is crucial as it is to be done with energy efficiency and minimize discovery latency and maximize percentage of neighbours discovered. The current ND approaches that are indirect in nature are categorized into methods of removal of active slots from wake-up schedules and intelligent addition of new slots. The two methods are found to have certain drawbacks. The first category disturbs original integrity of wake-up schedules leading to reduced chances of discovering new nodes in WSN as neighbours. When second category is followed, it may have inefficient slots in the wake-up schedules leading to performance degradation. Therefore, the motivation behind the work in this paper is that by combining the two categories, it is possible to reap benefits of both and get rid of the limitations of the both. Making a hybrid is achieved by introducing virtual nodes that help maximize performance by ensuring original integrity of wake-up schedules and adding of efficient active slots. Thus a Hybrid Approach to Neighbour Discovery (HAND) protocol is realized in WSN. The simulation study revealed that HAND outperforms the existing indirect ND models.


Cite This Article

S. Mekala and K. Shahu Chatrapati, "A hybrid approach to neighbour discovery in wireless sensor networks," Intelligent Automation & Soft Computing, vol. 35, no.1, pp. 581–593, 2023.

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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