A Polynomial Series-Based Data Aggregation and Spectrum Aware Clustering Technique for a Combined Model of WSN and Cognitive Radios in IoT Applications

International Journal of Electrical and Electronics Engineering

© 2024 by SSRG - IJEEE Journal

Volume 11 Issue 7

Year of Publication : 2024

Authors : Shivaraj Sharanabasappa Kalburgi, M. Manimozhi

10.14445/23488379/IJEEE-V11I7P123

How to Cite?

Shivaraj Sharanabasappa Kalburgi, M. Manimozhi, "A Polynomial Series-Based Data Aggregation and Spectrum Aware Clustering Technique for a Combined Model of WSN and Cognitive Radios in IoT Applications," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 7, pp. 258-270, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I7P123

Abstract:

The demand for wireless communication has surged due to the rise of IoT applications. Wireless Sensor Networks (WSNs) are crucial in this field but often operate in license-free spectrums, causing interference and impacting Quality of Service (QoS). Cognitive Radio (CR) technology offers a solution by enabling opportunistic access to licensed bands, thus reducing interference and enhancing system performance. However, integrating CR with IoT and WSNs poses challenges due to the high energy consumption of CR tasks and limited power and computation resources in sensor networks. Continuous data collection also leads to redundancy. To address these issues, data aggregation techniques can eliminate redundant data, and energy-aware routing can reduce energy consumption during data exchange. This study proposes a combined model of WSN and CR for IoT applications, utilizing a polynomial series-based data aggregation and spectrum-aware clustering technique. The proposed approach achieves a packet delivery rate of 95.47%, energy consumption of 5.216J, and a delay of 0.554 seconds, outperforming existing schemes in CRSNs.

Keywords:

Clustering, Cognitive Radios, Data aggregation, Spectrum management, Wireless Sensor Network.

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