Hybrid optimization routing management for autonomous underwater vehicle in the internet of underwater things

Abstract

Internet of Underwater Things (IoUTs) is completely embraced by acoustic sensor nodes that are commonly battery consumption. The sensor’s battery life is restricted and it is problematic while it needs to recharge. Moreover, these kinds of underwater sensor nodes may form the cluster to store the huge amount of energy. The cluster head formation is the main problem that the cluster head needs to use added energy for aggregation and data collection to broadcast the data packets to the destination. The autonomous underwater vehicles (AUVs) have to be used to connect the sensor nodes with the internet or particular devices, the path discovery within the AUV is the primary issue for producing the efficient routing in IoUTs. In this paper, the proposed routing strategy is used to provide energy proficiency while performing the cluster-based routing. AUV is responsible for selecting the cluster head and maintaining cluster-based scheduling. The AUV path is constructed to increase the residual energy for the sensor nodes in the network. It coordinates the AUV’s effective way of arranging calculations into the steering convention. This incorporated specialized strategy depends on two stages: A-ANTD (AUV-Assisted Network Transmit Devising) and TARD (Transmit Assisted Route Devising). A-ANTD uses the collaboration of performance of multiple ventures to decrease energy utilization for the system and stays away from the problem area and sector issue with a vital GN (Gateway Nodules) plans. The experimental results show that the proposed methodology has improved performance compared with the other methods.