An Energy-Efficient Clustering Based Data Compression in Wireless Sensor Networks Using Fuzzy Logic and Compressive Sensing
Rachit Manchanda · 2024
Wireless sensor networks (WSNs) face numerous challenges due to fixed resources of energy and communication overhead due to redundant data. This work explains FLEC-CS (Fuzzy Logic Energy-Efficient Clustering based Compressive Sensing), a hybrid approach which increases energy efficiency and manage the data in WSNs. The proposed protocol make use of fuzzy logic (FL) to dynamically choose cluster heads (CHs) which depends on the node parameters such as its residual energy, distance from the base station (BS), and Node density to reduce consumption of energy and to improve lifespan of the network. Furthermore, Compressive Sensing (CS) reduces the duplicity of data inside the clusters by exploiting the sparse nature of the sensed data which lowers down the CH communication overhead and saves the energy. The simulation observation shows that FLEC-CS outperforms standard clustering and data reduction approaches in terms of stability of the network, its survival period and the throughput. The proposed protocol increases the scalability and flexibility of WSNs while also ensuring minimum resource utilisation and reliable transmission of data. This approach is quite advantageous for Internet of Things (IoT) based applications which require constant working of sensor network processes. FLEC-CS protocol integrates fuzzy logic-based clustering with compressive sensing which is considered to be a vital approach to increase the performance of the network and to prolong the operational lifespan of WSNs.