为避免舰船编队通信网络在数据传输时出现网络堵塞和冲突,提高数据传输速率,研究舰船编队通信网络混合数据智能调度方法。分析舰船编队通信网络结构,根据舰船通信网络状态,构建混合数据智能调度优化目标函数,基于深度学习网络的优化方法,获取最佳混合数据智能调度方案。经实验验证可知,该方法可有效降低混合数据传输时延与路由开销,提高分组投递率,避免通信网络发生堵塞现象。
To avoid network congestion and conflicts during data transmission in the ship formation communication network, and improve the data transmission rate, a hybrid data intelligent scheduling method for ship formation communication network is studied. Analyze the communication network structure of ship formation, and construct a mixed data intelligent scheduling optimization objective function based on the status of ship communication network. Based on deep learning network optimization methods, obtain the optimal mixed data intelligent scheduling scheme. Experimental verification shows that this method can effectively reduce mixed data transmission delay and routing overhead, improve packet delivery rate, and avoid communication network congestion.
2023,45(24): 176-179 收稿日期:2023-08-31
DOI:10.3404/j.issn.1672-7649.2023.24.032
分类号:TN913
作者简介:刘绪军(1974-),男,高级工程师,研究方向为计算机网络、实时计算机应用、计算机图形学、网络管理与安全、计算机图形学及信息可视化
参考文献:
[1] 董然, 孙创, 傅强, 等. 基于非线性干扰观测器的舰船编队控制方法[J]. 哈尔滨工程大学学报, 2022, 43(5): 697-705.
DONG Ran, SUN Chuang, FU Qiang, et al. A ship formation control method using a nonlinear disturbance observer[J]. Journal of Harbin Engineering University, 2022, 43(5): 697-705.
[2] 王丽媛, 郭树生, 安吉祥. 基于枚举法的海上风电智能运维调度模型[J]. 舰船工程, 2022, 44(2): 28−34.
WANG Liyuan, GUO Shusheng, AN Jixiang . Intelligent operation and maintenance dispatching model of offshore wind power based on the enumeration method [J]. Ship Engineering 2022, 43(5): 697−705.
[3] 杨晨, 邓茹凤, 张宏, 等. 基于网络通信的设备互操和数据热备份的设计方法[J]. 船海工程, 2022, 15(5): 11-14.
YANG Chen, DENG Ru-feng, ZHANG Hong, et al. Design Method for equipment interoperation and data hot-backup based on network communication[J]. Ship & Ocean Engineering, 2022, 15(5): 11-14.
[4] 杨毅, 熊鹰. 基于云计算平台的多数据库并行调度算法仿真[J]. 计算机仿真, 2023, 40(6): 459-462+527.
YANG Yi, XIONG Ying. Simulation of multi database parallel scheduling algorithm based on cloud computing platform[J]. Computer Simulation, 2023, 40(6): 459-462+527.
[5] 王然, 张宇超, 王文东, 等. 基于预测的数据中心间混合流量调度算法[J]. 计算机研究与发展, 2021, 58(6): 1307-1317.
WANG Ran, ZHANG Yuchao, WANG Wendong, et al. Algorithm of mixed traffic scheduling among data centers based on prediction[J]. Journal of Computer Research and Development, 2021, 58(6): 1307-1317.
[6] 牟军敏, 郭绍卿, 张志江, 等. 基于AIS数据的水域航路网络提取方法[J]. 中国航海, 2023, 46(2): 152-160.
MOU Junmin, GUO Shaoqing, ZHANG Zhijiang, et al. Extraction of ship track pattern from AIS data[J]. Navigation of China, 2023, 46(2): 152-160.
[7] 白响恩, 李博翰, 徐笑锋, 等. 基于AIS数据的航运物流港口调度优化研究[J]. 包装工程, 2023, 44(5): 211-221.
BAI Xiang-en, LI Bo-han, XU Xiao-feng, et al. Scheduling Optimization of shipping logistics port based on AIS data[J]. Packaging Engineering, 2023, 44(5): 211-221.
[8] 王栽毅, 杨照. 船联网智能数据传输与通信算法研究[J]. 中国海洋大学学报(自然科学版), 2021, 51(7): 108-114.
WANG Zaiyi, YANG Zhao. Research on intelligent data transmission and communication algorithms for ship networking[J]. Periodical of Ocean University of China, 2021, 51(7): 108-114.