EENC - energy efficient nested clustering in UASN
Syed Hassan Ahmed, Abdul Wahid, Dongkyun Kim · 2014
Energy efficiency in Underwater Acoustic Sensor Network (UASN) is a key challenge for extending network lifetime. Base on analysis of energy consumption for LEACH in underwater channel, we propose a novel clustering scheme for UASN based on grouping nodes to ensure that nodes balance energy load by considering residual energy of candidate nodes. We introduce a formation of small clusters (groups) within clusters named as Nested Clustering (NC). Our Energy Efficient Nested Clustering (EENC) scheme divides each cluster into small groups and nodes in each of those small groups switch their operation modes (idle and awake) to achieve energy efficiency. Through simulation results, it is observed that our proposed EENC scheme has better network lifetime and optimized data duplication as compared to the existing clustering schemes.