Energy Efficient Cognitive Wireless Sensor Network for Loud Noise Detection
Anastasiia Yatsenko, Anzhelika Parkhomenko, Artem Tulenkov, Carsten Wolff, Illia Parkhomenko, Oleg Pozdnyakov · 2024
The development of small, autonomous sensor devices and their integration into wireless sensor networks has resulted in robust, easy-to-deploy and easy-to-operate systems that are used in a wide range of applications. However, despite the obvious advantages, a number of problems need to be solved to ensure their long-term and uninterrupted operation. One of them is energy efficiency and uniform distribution of energy between the network nodes. Studies have shown that cognitive wireless sensor networks are able to adapt to the state and conditions of networks, take into account aspects such as nodes energy levels, and act accordingly. Among the adaptive protocols, LEACH is considered to be quite effective as it helps to reduce the energy consumption of the network, however, the cluster head selection is based on random approach, which may not be the most efficient way. This paper proposes a modification of the cluster head selection method that allows taking into account the energy of each network node. This approach will help to equalize the energy consumption of nodes and optimize the network workflow as a whole, increasing its reliability and service life.