为快速有效存储舰船监控网络异构监控数据，提出舰船监控网络异构监控数据存储方法。此方法主要用于优化舰船监控网络监控数据云存储平台的存储效果，多个舰船监控设备，经多个虚拟网关在数据接口层统一接口的使用下，将异构监控数据发送至数据处理层；数据处理层使用基于聚类的异构监控数据分类方法，将异构监控数据按照来源分类；分类后数据发送至分布式数据存储层，使用基于自适应分配的异构监控数据存储方法，结合分布式数据存储模型的可用容量与带宽状态，将分类后监控数据以自适应分配方式，存储于性能最优的存储模型，完成自适应分配存储。实验结果表明，此方法具备舰船监控网络异构监控数据自适应存储能力，存储效率、成功率显著提高。
To quickly and effectively store heterogeneous monitoring data in ship monitoring networks, a storage method for heterogeneous monitoring data in ship monitoring networks is proposed. This method is mainly used to optimize the storage effect of the ship monitoring network monitoring data cloud storage platform. Multiple ship monitoring devices send heterogeneous monitoring data to the data processing layer through multiple virtual gateways under the unified interface of the data interface layer. The data processing layer uses a clustering based heterogeneous monitoring data classification method to classify heterogeneous monitoring data by source. After classification, the data is sent to the distributed data storage layer. Using a heterogeneous monitoring data storage method based on adaptive allocation, combined with the available capacity and bandwidth status of the distributed data storage model, the classified monitoring data is adaptively allocated and stored in the storage model with the best performance, completing the adaptive allocation and storage. The experimental results show that this method has the ability to adaptively store heterogeneous monitoring data in ship monitoring networks, with significant storage efficiency and success rate.
2023,45(12): 136-139 收稿日期：2023-02-22
DOI：10.3404/j.issn.1672-7619.2023.12.026
分类号：TP391
基金项目：湖北理工学院校级项目（22xjz03Y）
作者简介：李辉燕(1980-),女,讲师,研究方向为网络工程、大数据及数据挖掘
参考文献：
[1] 胡琦, 朱国情, 陈于涛. 船舶监控系统运行数据抽取与分析方案设计[J]. 船海工程, 2020, 49(3): 112–116+120
[2] 毕振波, 张世友, 杨花, 等. 基于浅层机器学习的视频监控船舶检测综述[J]. 系统仿真学报, 2021, 33(12): 2792–2807
[3] 卢运娇, 罗思思. 木质渔船机舱水位监控系统设计[J]. 船海工程, 2020, 49(1): 90–93
[4] 周毅, 李萌, 张海涛, 等. 船岸一体化数据管理系统的网络安全技术[J]. 船海工程, 2021, 50(3): 73–76
[5] 李鸿飞, 杜溢墨, 曾熠, 等. 异构混合存储的软硬件协同数据放置策略[J]. 国防科技大学学报, 2020, 42(2): 64–71
[6] 沈志宏, 赵子豪, 王华进, 等. PandaDB: 一种异构数据智能融合管理系统[J]. 软件学报, 2021, 32(3): 763–780
[7] 孙超, 肖文名, 曾乐, 等. 海量监视数据云存储服务模型的设计与实现[J]. 武汉大学学报(信息科学版), 2020, 45(7): 1099–1106
