Data Collection in Underwater Sensor Networks based on Mobile Edge Computing
Data Collection in Underwater Sensor Networks based on Mobile Edge Computing
复制标题
基于移动边缘计算的水下传感器网络数据采集
DOI：
10.1109/access.2019.2918213
复制
发表时间：
2019-01-01
期刊：
影响因子：
3.9
通讯作者：
Liu, Xuxun
中科院分区：
文献类型：
--
作者：
Cai, Shaobin;Zhu, Yong;Liu, Xuxun
随着边缘设备和无线技术的快速发展，水下无线传感器网络正处于蓬勃发展的过程中。传统的多跳数据采集方式存在功耗高、功耗严重不均衡等缺点，近年来，移动的边缘单元（如自主水下航行器（AUV））被广泛应用于水下数据采集，以解决能耗不均衡问题。然而，现有的方法没有充分考虑水下环境下AUV的高效移动的边缘计算和真实的移动模型。在本文中，我们提出了一个数据收集方案的基础上的移动模型的移动的边缘元素在水中。该模型充分考虑了水下机器人的运动方向和运动速度，接近于水下机器人在稳定三维环境中的运动特性。利用AUV的计算、存储和移动能力，设计了一种目标选择算法，用于计算AUV数据采集的移动路径。理论分析和实验结果表明，该方法提高了数据采集效率，降低了节点功耗，延长了网络生存时间。
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.