Data Collection in Underwater Sensor Networks based on Mobile Edge Computing

With the rapid developments in edge devices and wireless technologies, the underwater wireless sensor networks (UWSNs) are in the process of vigorous development. In UWSNs, the traditional multi-hop data collection methods have some disadvantages such as high power consumption, severe unbalance in power consumption, and so on. In recent years, mobile edge elements (such as an autonomous underwater vehicle, AUV) are widely used in underwater data collection to solve energy consumption imbalance problems. However, the existing methods do not fully consider the efficient mobile edge computing and the real mobility model of AUV in the underwater environment. In this paper, we propose a data collection scheme based on a mobility model of mobile edge elements under water. In this model, the mobility direction and velocity are fully considered, which are close to the mobility characteristic of AUVs in the stable 3D environment. By using computing, storage, and mobility abilities of AUVs, a target selection algorithm is designed to calculate the mobility path of data collection for AUV. The theoretical analysis and experimental results show that the proposed method improves the efficiency of data collection, reduces the power consumption of nodes, and extends the network lifetime.