A Two-Level Clustering based on Position, Data Correlation and Residual Energy in WSN
Marwa Fattoum, Zakia Jellali, Leı̈la Najjar Atallah · 2019
Clustering WSN nodes has been a key solution to reduce the energy consumption of sensor nodes and thus to prolong the network lifetime. A new two-level clustering algorithm is here proposed. It first exploits data measurement correlation and sensor nodes' locations to partition the network into sub-regions with highly correlated data. Second, a residual energy based clustering is performed to divide each region into clusters. The simulation results show that our clustering scheme, which is a combination of two steps, outperforms LEACH as well as the dissociated two steps, based either on correlation (Step1) or on residual energy (Step2), in terms of energy consumption and network lifetime.