DDCA: A Dynamic Data Collection Algorithm in Mobile Underwater Wireless Sensor Networks

In underwater monitoring systems, it is important to guarantee high availability of the data collection service. An effective approach is the use of autonomous underwater vehicles (AUVs) to gather data from the sensor nodes. In mobile underwater wireless sensor networks, node locations change continuously, which increases the difficulty of data collection. In this paper, a dynamic data collection algorithm based on mobile nodes (DDCA) is proposed to collect underwater data. AUVs can move directly to the predicted node location to shorten the time of data collection. The algorithm is divided into two parts: mobility prediction and data collection. The locations of the mobility sensor nodes are predicted, and then the trajectory of the AUV is planned according to the predicted locations of sensor nodes to achieve reliable data collection. Furthermore, a region partitioning strategy is proposed to reduce the time difference of each AUV completing the data collection. The simulation results demonstrate that the DDCA effectively reduces the time of data collection and shortens the time difference of AUVs returning to the sink node.