Power Management using Neural Networks for Wireless Sensor Network

Shri Anil Dattatraya Nimbalkar *
Department of Electronics & Telecommunication Engineering, Kolhapur Institute of Technology's College of Engineering (Autonomous), Kolhapur, Maharashtra, India.
Periodicity:July - December'2021


Intelligent analysis is used to process the structure of a wireless sensor network (WSN) and produce some information that can be used to improve the performance of the WSN's management applications. This paper introduces a new approach for wireless sensor networks which is based on neural networks. The presented work is an intelligent method based on the existing concept of multi-agent systems for WSN management. The proposed work shows a performance improvement. Wireless sensor networks need to be managed in different ways, e.g. power consumption of each sensor, efficient data routing without redundancy, control of data reading and sending intervals, etc. The random distribution of wireless sensors, the numerous variables that affect the operation of the WSN, and the uncertainty of various algorithms (for example, self-localization of sensors) make the WSN fuzzy. Given this fuzzy nature and numerous details, a neural network is an ideal tool to use to cover these details, which are so difficult to detect and explicitly, model. This paper presents a neural network-based approach, which results in more efficient routing path discovery and sensor power management.


Wireless Sensor Network (WSN), Power Management, Routing, Neural Networks, Agents.

How to Cite this Article?

Nimbalkar, S. A. D. (2021). Power Management using Neural Networks for Wireless Sensor Network. i-manager’s Journal on Wireless Communication Networks, 10(1), 20-27.


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