Fuzzy Logic-based Two-Level Clustering for Data Aggregation in WSN
Marwa Fattoum, Zakia Jellali, Leı̈la Najjar Atallah · 2020
In Wireless Sensor Network (WSN) design, the energy factor is the most critical issue due to the limited capacity of the sensor nodes power sources. The clustering is one of the most representative approaches for reducing the energy consumption in large scale WSN. This paper suggests a new two levels energy efficient clustering approach based on fuzzy logic model to improve the network lifetime. A two-level clustering scenario is considered in which fuzzy logic is applied in both Step1 and Step2 for respectively cluster head (CH) selection and cluster formation processes. The proposed model uses similarity parameters: similarity difference rate and similarity coverage rate, to measure the spatial correlation of data in the network, the distance parameters: closeness to CH, closeness to the sink and the residual energy as fuzzy logic inputs. Comparing the new proposed fuzzy logic based clustering to other schemes and variants of clustering approaches through simulation shows its better performance in terms of energy consumption and network lifetime extension.