-
摘要:
航空电子系统随着任务需求和技术的发展不断向深度综合演进,其系统的复杂性给网络的设计和验证带来了巨大的挑战,如何通过网络生成实现受限资源条件下航电信息交互的实时性能保障是目前亟待解决的问题。针对目前存在的无法对航电网络进行实时性调控的拓扑设计方法进行改进,依据终端节点之间所有虚拟链路的最大通信帧长之和的大小关系,提出一种基于度中心性理论的航空电子全双工交换式以太网(AFDX)网络拓扑生成算法。将终端节点之间数据帧长作为节点度的衡量标准,对所有终端节点进行集合划分,并根据集合中终端节点的数据帧长对交换机进行连接。采用确定性网络演算以及仿真的方法对基于度中心性的AFDX网络拓扑生成算法进行效能评估。利用确定性网络演算方法,在小规模虚拟链路(VL)的组网下,结果显示:基于度中心性的拓扑生成算法生成的网络拓扑中75%的VLs实时性能优于原始人工设计的网络拓扑,且端到端延迟平均减小9.37%。利用OMNet++仿真方法,在1 400条虚拟链路的组网规模下,结果显示:基于度中心性的拓扑生成算法生成的网络拓扑中94.3%的VLs实时性能优于人为规划网络拓扑,且端到端延迟平均减小50.2%。由此表明:基于度中心性的拓扑生成算法很大程度上提高了网络的实时性能保障。
-
关键词:
- 网络拓扑生成 /
- 度中心性 /
- 确定性网络演算 /
- 航空电子全双工交换式以太网(AFDX) /
- 实时性
Abstract:With the development of mission requirements and technologies, avionics systems continue to evolve into deep integration, and the complexity of systems has brought enormous challenges to the design and verification of networks. How to realize real-time performance guarantee of avionics information interaction through network generation under restricted resources is an urgent problem to be solved. According to the relationship between the sum of the maximum communication frame lengths of all virtual links between terminal nodes, the avionics full duplex switched Ethernet (AFDX) network topology generation algorithm based on degree centrality theory is proposed to improve the existing topology design method that cannot control the avionics network in real time. All the terminal nodes are collectively divided according to the data frame length between the terminal nodes which is used as a measure of the degree of the node. The switch performs dynamic connection according to the data frame length of the terminal node in the set. Deterministic network calculus and simulation methods are used for performance evaluation of AFDX network topology generation algorithm based on degree centrality. The results show that 75% of the VLs' real-time performance in the network topology based on degree centrality is better than the original artificially designed network topology using the deterministic network calculus method under the networking of small-scale virtual link, and the end-to-end delay is reduced by on average of 9.37%. The results show that 94.3% of VLs real-time performance in the network topology based on degree centrality is better than the artificially planned network topology. And the end-to-end delay is reduced by 50.2% on average using the OMNet++ simulation method under the networking scale of 1 400 virtual links. Therefore, the results show that the topology generation algorithm based on degree centrality greatly improves the real-time performance guarantee of the network.
-
表 1 网络参数配置信息
Table 1. Network parameter configuration information
VL 源节点 目的节点 每条VL最大通信帧长/Byte BAG/ms 1~50 1 3 540 128 51~100 1 5 334 32 101~110 1 23 200 32 111~160 2 9 1510 64 161~210 2 17 55 64 211~260 2 24 100 32 261~280 2 4 144 32 281~330 4 7 670 8 331~380 4 19 126 4 381~430 5 20 203 4 431~480 6 16 132 16 481~530 6 23 411 16 531~560 7 6 90 16 561~590 7 19 46 2 591~620 8 11 76 32 621~680 8 17 23 64 681~730 10 2 258 64 731~780 10 8 560 32 781~810 11 9 640 8 811~840 11 8 710 32 841~870 13 16 861 16 871~880 14 12 96 16 881~900 15 13 147 64 901~1000 18 21 100 128 1001~1100 22 6 460 128 1101~1200 24 11 200 32 1201~1300 16 21 340 32 1301~1400 17 14 260 32 表 2 网络演算配置信息
Table 2. Network calculus configuration information
VL 源节点 目的节点 每条VL最大通信帧长/Byte BAG/ms 1~5 1 3 540 128 111~116 2 9 1510 64 161~165 2 17 55 64 381~385 5 20 203 4 431~435 6 16 132 16 561~565 7 19 46 2 781~785 11 9 640 8 871~875 14 12 96 16 1101~1105 24 11 200 32 1301~1305 17 14 260 128 -
[1] WANG H C, NIU W S.Design and analysis of AFDX network based high-speed avionics system of civil aircraft[J]. Advanced Materials Research, 2012, 462:445-451. doi: 10.4028/www.scientific.net/AMR.462.445 [2] SUTHAPUTCHAKUN C, SUN Z, KAVADIAS C, et al.Performance analysis of AFDX switch for space onboard data networks[J]. IEEE Transactions on Aerospace & Electronic Systems, 2016, 52(4):1714-1727. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=ee9cda97144bd3a8c807539f9722cc32 [3] SHENG L, GUANG X, CHEN F, et al.A review on complex network dynamics in evolutionary algorithm[C]//IEEE Trustcom/BigDataSE/ISPA.Piscataway, NJ: IEEE Press, 2017: 2221-2226. http://www.researchgate.net/publication/313543668_A_Review_on_Complex_Network_Dynamics_in_Evolutionary_Algorithm [4] BATOOL K, NIAZI M A.Modeling the internet of things:A hybrid modeling approach using complex networks and agent-based models[J]. Complex Adaptive Systems Modeling, 2017, 5(1):1-4. doi: 10.1186/s40294-016-0040-9 [5] DOU B L, ZHANG S Y.Model for congestion dynamics on complex networks with traffic-awareness routing strategy[C]//20108th World Congress on Intelligent Control and Automation.Piscataway, NJ: IEEE Press, 2010: 5325-5330. http://www.researchgate.net/publication/238517086_model_for_congestion_dynamics_on_complex_networks_with_traffic-awareness_routing_strategy?ev=auth_pub [6] 杨海涛.复杂信息网络性能设计[M].北京:中国宇航出版社, 2014:39-50.YANG H T.Complex information network performance design[M]. Beijing:China Aerospace Publishing House, 2014:39-50(in Chinese). [7] ANDRES V, LLOPIS L J.Topology control for wireless mesh networks based on centrality metrics[C]//Proceedings of the 10th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks, 2013: 25-32. [8] RACHMAN Z A, MAHARANI W.The analysis and implementation of degree centrality in weighted graph in social network analysis[C]//2013 International Conference of Information and Communication Technology (ICoICT), 2013: 72-76. [9] PIOTR B, SKIBICKI K, KAZIENKO P, et al.A degree centrality in multi-layered social network[C]//International Conference on Computational Aspects of Social Networks.Piscataway, NJ: IEEE Press, 2011: 19-21. http://www.oalib.com/paper/4035130 [10] 黄臻, 张勇涛, 熊华钢.基于离散事件方法的AFDX建模与仿真[J].北京航空航天大学学报, 2011, 37(10):1326-1333. https://bhxb.buaa.edu.cn/CN/abstract/abstract12113.shtmlHUANG Z, ZHANG Y T, XIONG H G.AFDX modeling and simulation based on discrete event method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2011, 37(10):1326-1333(in Chinese). https://bhxb.buaa.edu.cn/CN/abstract/abstract12113.shtml [11] 赵琳, 何锋, 熊华钢.航空电子AFDX与AVB传输实时性抗干扰对比[J].北京航空航天大学学报, 2017, 43(12):2359-2369. https://bhxb.buaa.edu.cn/CN/abstract/abstract14271.shtmlZHAO L, HE F, XIONG H G.Comparison of real-time anti-jamming transmission for avionics AFDX and AVB[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(12):2359-2369(in Chinese). https://bhxb.buaa.edu.cn/CN/abstract/abstract14271.shtml [12] ZHANG X, WANG Y.Research of AFDX network delay based on modified network calculus[C]//IEEE International Conference on Network Infrastructure & Digital Content.Piscataway, NJ: IEEE Press, 2012: 178-181. http://www.researchgate.net/publication/261236734_Research_of_AFDX_network_delay_based_on_modified_network_calculus [13] SONI A, LI X, SCHARBARG J L, et al.Work in progress paper: Pessimism analysis of network calculus approach on AFDX networks[C]//International Symposium on Industrial Embedded Systems (SIES).Piscataway, NJ: IEEE Press, 2017: 1-4. [14] MOY M, ALTISEN K.Arrival curves for real-time calculus: The causality problem and its solutions[C]//International Conference on Tools & Algorithms for the Construction & Analysis of Systems, 2010: 358-372. http://www.springerlink.com/content/r3616574876751g1 [15] CIUCU F, BURCHARD A.A network service curve approach for the stochastic analysis of networks[J]. ACM Sigmetrics Performance Evaluation Review, 2005, 33(1):279-290. doi: 10.1145/1071690.1064251 [16] BAUER H, SCHARBARG J L, FRABOUL C.Improving the worst-case delay analysis of an AFDX network using an optimized trajectory approach[J]. IEEE Transactions on Industrial Informatics, 2010, 6(4):521-533. doi: 10.1109/TII.2010.2055877 [17] REJEB N, SALEM A K, SAOUD S B.AFDX simulation based on TTEthernet model under OMNeT++[C]//2017 International Conference on Advanced Systems and Electric Technologies(IC_ASET).Piscataway, NJ: IEEE Press, 2017: 423-429.