Non Linear Grid Based Search Energy Optimization for AUV Aided Underwater Acoustic Sensor Network

Recently, the significance of the Underwater Acoustic Sensor Network (UWASN) attracts the researchers due to the huge benefits of data collection obtained from the sensor nodes under the ocean. Resource exploration in underwater uses a sensor node for data sensing, collecting, processing and forwarding. These sensor nodes are energy constrained and often depleted, then becomes inactive. This occurrence may lead to network failure while computing optimal node selection, hence proposes non linear Grid-Based Search Energy Optimization (GBSEO) algorithm to find the optimal forwarding node with Autonomous Underwater Vehicle (AUV). The GBSEO algorithm considers the underwater Doppler Effect, sedimental drift and water current based on non linear searching and thereby improves the overall efficiency of the network by optimizing the energy of sensor nodes. AUV utilizes non linear optimization to improve the path selection based on GBSEO and thereby increases the network lifetime, energy efficiency and reduces the time delay. The results show that the proposed GBSEO algorithm outperforms the traditional algorithm Clustering Algorithm Optimization (CAO).