为实时传输海量船舶图像，为有效监控船舶实时航行状况提供保障，研究基于云计算的船舶图像网络数据低时延传输方法。结合云计算技术，构建船舶图像网络数据传输平台，通过平台数据接收单元将大量船舶网络数据存入云端服务器内；数据处理单元基于云计算的分布式处理特点，结合并行运行框架Map Reduce和并行化K-means聚类算法，并行挖掘云端服务器内的船舶图像网络数据；信道均衡单元结合所构建的船舶通信网络节点能量消耗模型，均衡船舶通信网络信道，运用均衡信道实现所挖掘船舶图像网络数据的传输。结果显示，该方法的数据挖掘速率高，数据传输过程中各信道能量开销均衡，且可低至3.5 kJ，传输船舶图像网络数据的时延可低至10.23 ms，实现了数据的低时延传输。
Real time transmission of massive ship images provides a guarantee for effectively monitoring the real-time navigation status of ships. Research on low latency transmission methods for ship image network data based on cloud computing. Combining cloud computing technology, build a ship image network data transmission platform, and store a large amount of ship network data into cloud servers through the platform's data receiving unit. The data processing unit is based on the distributed processing characteristics of cloud computing, combined with the parallel running framework Map Reduce and the parallel K-means clustering algorithm, to parallelly mine the ship image network data in the cloud server; The channel equalization unit combines the energy consumption model of the constructed ship communication network nodes to balance the ship communication network channels, and uses the balanced channels to achieve the transmission of the mined ship image network data. The results show that this method has a high data mining rate, balanced energy overhead of each channel during data transmission, and can be as low as 3.5 kJ. The delay of transmitting ship image network data can be as low as 10.23 ms, achieving low delay transmission of data.
2024,46(16): 178-181 收稿日期：2024-02-22
DOI：10.3404/j.issn.1672-7649.2024.16.031
分类号：TP393
基金项目：河南省科技攻关资助项目（232102320318）
作者简介：李小丽（1983 – ），女，硕士，讲师，研究方向为计算机应用与算法
参考文献：
[1] 陈立家, 周为, 许毅, 等. 一种基于SDN的多约束无人船网络传输路由算法[J]. 中国船舶研究, 2022, 17(4): 107-113.
CHEN Lijia, ZHOU Wei, XU Yi, et al. Multi-constrained unmanned surface vessel network transmission routing algorithm based on SDN[J]. Chinese Ship Research, 2022, 17(4): 107-113.
[2] 徐志威, 毕美华, 季晨阳, 等. 支持多业务共存的Xhaul网络低时延带宽分配算法[J]. 光通信技术, 2022, 46(5): 15-19.
XU Zhiwei, BI Meihua, JI Chenyang, et al. Low-delay bandwidth allocation algorithm for xhaul networks supporting multi-service coexistence[J]. Optical Communication Technology, 2022, 46(5): 15-19.
[3] 许方敏, 史文策, 冯涛, 等. 基于联合波束赋形的无人机辅助通信网络上行传输技术[J]. 电子与信息学报, 2022, 44(3): 871-880.
[4] 郝奕, 黄雷. C-V2X网络下基于传输损失函数的数据传输策略[J]. 电信科学, 2023, 39(12): 65-75.
[5] 刘琪华, 梅佳雪, 王金栋, 等. 基于锁模光学频率梳的高速数据传输[J]. 物理学报, 2024, 73(4): 184-191.
[6] MA Wenqi, LU Huimin, CHEN Danyang, et al. Orbital angular momentum underwater wireless optical communication system based on convolutional neural network[J]. Journal of optics, 2022, 24(6): ARTN 065701-065709.
