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Data Collection Scheme for Underwater Sensor Cloud System Based on Fog Computing

机译:基于雾计算的水下传感器云系统数据采集方案

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The scheme design of data collection for Underwater Acoustic Sensor Networks (UASNs) poses many challenges due to long propagation, high mobility, limited bandwidth, multi-path and Doppler Effect. In this paper, unlike the traditional underwater sensor network architecture (single sink or multi-sink), we proposed a novel underwater sensor cloud system based on fog computing in view of time-critical underwater applications. In such an architecture, fog nodes with great computation and storage capacity are responsible for computing, dimension reduction and redundant removal for data collected from physical sensor nodes, and then transfer the processed and compressed data to surface center sink node. After that, the center sink sends the received data from fog nodes to cloud computing center. In addition, in this paper we present distance difference and waiting area-based routing protocol, called DDWA. Finally, in comparison with RDBF, naive flooding and HH-VBF, we conduct extensive simulations using NS-3 simulator to verify the effectiveness and validity of the proposed data collection scheme in the context of the proposed architecture.
机译:水下声传感器网络(UASN)的数据收集方案设计由于传播时间长,移动性高,带宽有限,多径和多普勒效应而面临许多挑战。在本文中,与传统的水下传感器网络体系结构(单接收器或多接收器)不同,我们针对时间紧迫的水下应用提出了一种基于雾计算的新型水下传感器云系统。在这样的体系结构中,具有大量计算和存储能力的雾节点负责对从物理传感器节点收集的数据进行计算,降维和冗余删除,然后将经过处理和压缩的数据传输到地表中心汇聚节点。之后,中心接收器将接收到的数据从雾节点发送到云计算中心。另外,在本文中,我们提出了距离差和基于等待区域的路由协议,称为DDWA。最后,与RDBF,天真洪水和HH-VBF相比,我们使用NS-3仿真器进行了广泛的仿真,以验证所提出的体系结构中所提出的数据收集方案的有效性和有效性。

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