HAS⁴: A Heuristic Adaptive Sink Sensor Set Selection for Underwater AUV-Aid Data Gathering Algorithm

Area of Science:

• Robotics and Autonomous Systems
• Underwater Sensor Networks
• Wireless Communication Technologies

Background:

• Underwater wireless sensor networks (UWSNs) face challenges in timely data retrieval.
• Autonomous underwater vehicles (AUVs) can serve as mobile data mules for periodic data collection.
• Efficient data gathering is crucial for various underwater applications.

Purpose of the Study:

• To address the data gathering problem in UWSNs.
• To optimize the selection of sensors visited by AUVs for efficient data collection.
• To enhance network lifetime and reduce operational costs.

Main Methods:

• Deployment of autonomous underwater vehicles (AUVs) as mobile data collectors.
• Utilizing a novel high-speed magnetic-induction communication system between AUVs and sensor nodes.
• Employing acoustic communication for data transmission from non-visited sensors to visited ones.
• Implementation and evaluation of the HAS 4 (Heuristic Adaptive Sink Sensor Set Selection) algorithm.

Main Results:

• The HAS 4 algorithm demonstrates superior performance compared to benchmark selection methods.
• HAS 4 effectively contributes to energy saving within the sensor network.
• The algorithm aids in reducing the operational cost associated with AUV deployment.
• Network lifetime is prolonged through the optimized sensor selection strategy.

Conclusions:

• The HAS 4 algorithm is an effective solution for data gathering in UWSNs.
• Optimized sensor selection using HAS 4 leads to significant energy savings and extended network life.
• The proposed method offers a practical approach for improving the efficiency of underwater data collection.