基于度中心性的AFDX网络拓扑生成

王智宇; 何锋; 谷晓燕

doi:10.13700/j.bh.1001-5965.2019.0123

基于度中心性的AFDX网络拓扑生成

doi: 10.13700/j.bh.1001-5965.2019.0123

1.
北京航空航天大学电子信息工程学院, 北京 100083
2.
北京信息科技大学信息管理学院, 北京 100192

基金项目:

国家自然科学基金 71701020

装备预研领域基金 61403120404

中国民航大学天津市民用航空器适航与维修重点实验室开放基金 2017SW02

北京信息科技大学“勤信英才”培养计划 QXTCPC201707

详细信息

作者简介:
王智宇  女, 硕士研究生。主要研究方向:实时网络

何锋  男, 博士, 副教授。主要研究方向:航空电子综合、实时调度、实时网络

谷晓燕   女, 博士, 副教授。主要研究方向:复杂网络、数据分析与智能决策、风险管理

通讯作者:
何锋. E-mail:robinleo@buaa.edu.cn

中图分类号: V247;TP393
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- 被引次数: 0
出版历程
- 收稿日期: 2019-03-22
- 录用日期: 2019-07-05
- 网络出版日期: 2019-11-20

AFDX network topology generation based on degree centrality

WANG Zhiyu¹,
HE Feng^{1
, ,},
GU Xiaoyan²

1.
School of Electronic and Information Engineering, Beihang University, Beijing 100083, China
2.
School of Information Management, Beijing Information Science&Technology University, Beijing 100192, China

Funds:

National Natural Science Foundation of China 71701020

Equiprnent Per-Research Field Foundation 61403120404

Open Found of Tianjin Civil Aircraft Airworthiness and Maintenance Key Laboratory of Civil Aviation University of China 2017SW02

Qin Xin Talents Cultivation Program of Beijing Information Science & Technology University QXTCPC201707

More Information

Corresponding author: HE Feng.E-mail:robinleo@buaa.edu.cn

摘要

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。
- 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.
- network topology generation /
- degree centrality /
- deterministic network calculus /
- avionics full duplex switched Ethernet (AFDX) /
- real-time performance

HTML全文

图 1 端系统模型抽象图^[10]

Figure 1. Schematic of end system model^[10]

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图 2 一组交换机端口模型图^[10]

Figure 2. One set of switch port models^[10]

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图 3 核心处理节点集合划分流程图

Figure 3. Core processing node set division flowchart

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图 4 基于度中心性的AFDX网络拓扑生成算法

Figure 4. AFDX network topology generation algorithm based on degree centrality

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图 5 人为规划网络拓扑

Figure 5. Artificially designed network topology

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图 6 算法生成网络拓扑

Figure 6. Algorithm generated network topology

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图 7 确定性网络演算分析模型

Figure 7. Deterministic network calculus analysis model

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图 8 网络演算对比人为规划网络拓扑和算法生成拓扑最坏端到端延迟

Figure 8. Network calculus comparison of the worst end-to-end delay between artificially designed network topology and algorithm generated network topology

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图 9 人为规划拓扑和算法生成拓扑平均端到端延迟仿真对比

Figure 9. Simulation comparison of average end-to-end delay between artificially designed network topology and algorithm generated topology

下载: 全尺寸图片幻灯片

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

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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

下载: 导出CSV

参考文献(17)

[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.shtml HUANG 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.shtml ZHAO 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.