International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Hybrid Machine Learning-Based Energy Efficient Pathway in Wireless Sensor Networks for IoT Applications |
|---|---|
| ABSTRACT | Wireless Sensor Networks (WSNs) play a vital role in Internet of Things (IoT) applications such as environmental monitoring, smart cities, and industrial automation. However, the limited battery capacity of sensor nodes remains a major challenge, as frequent energy depletion directly affects network lifetime and data reliability. To discourse this concern, this paper proposes a Hybrid Machine Learning–based Energy Efficient Routing (HMLER) framework that integrates regression-based energy prediction with reinforcement learning–based routing optimization. The regression model estimates the future residual energy of sensor nodes using network parameters such as distance, load, and link quality, while the reinforcement learning agent dynamically selects optimal routing paths based on erudite reward policies. This hybrid approach enables accurate energy estimation and adaptive decision-making under dynamic network conditions. The proposed method is implemented and evaluated using the NS-3 simulator, considering metrics such as energy consumption, packet delivery ratio, end-to-end delay, and network lifetime. Recreation results demonstrate that the anticipated HMLER protocol significantly outperforms conventional routing schemes by improving energy efficiency, enhancing network stability, and extending operational lifetime, making it suitable for large-scale IoT- enabled WSN deployments. |
| AUTHOR | M.SATHISHKUMAR PhD Scholar, Department of Computer Science, Navarasam Arts & Science College for Women, Arachalur, Tamil Nadu, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404066 |
| pdf/66_Hybrid Machine Learning-Based Energy Efficient Pathway in Wireless Sensor Networks for IoT Applications.pdf | |
| KEYWORDS | |
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