| Citation: | SHI Yafei, LI Qiao, XIONG Huaganget al. Rate-constrained traffic prediction of TTE network based on LSTM[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(4): 822-829. doi: 10.13700/j.bh.1001-5965.2019.0320(in Chinese)
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The rate constraint (RC) traffic in time triggered Ethernet (TTE) is event-triggered traffic. In the application scenario of dynamic scheduling of RC traffic, if it can predict the sequence of several RC traffic arriving at the switching node in a short time in the future, the switching node can make scheduling decision in advance to reduce RC traffic delay and improve network throughput. In this paper, the arrival sequence model of RC traffic is established, and an algorithm of RC traffic prediction based on long-term memory network (LSTM) is proposed. Using OMNET++ tool to simulate TTE network, we can get the data of RC traffic transmission under multiple groups of mixed critical configuration, and train and test the prediction algorithm as an input sample. The experimental results show that the accuracy of LSTM algorithm in RC traffic prediction is more than 70%. The experimental results show that the proposed algorithm is suitable for RC traffic prediction scenarios.
| [1] |
熊华钢, 王中华.先进航空电子综合技术[M].北京:国防工业出版社, 2009:2-13.
XIONG H G, WANG Z H.Advanced avionics integrated technology[M].Beijing:National Defense Industry Press, 2009:2-13(in Chinese).
|
| [2] |
WOLFIG R, JAKOVLJEVIC M.Distributed IMA and DO-297: Architectural, communication and certification attributes[C]//Proceedings Digital Avionics Systems Conference.Piscataway, NJ: IEEE Press, 2008: 1.E.4-1-1.E.4-10.
|
| [3] |
SAE Aerospace. Time-triggered Ethernet: AS6802TM[S].Englewood, CO: SAE International, 2011.
|
| [4] |
STENER W, BAUER G, HALL B, et al.TTEthernet dataflow concept[C]//8th IEEE International Symposium on Network Computing and Applications.Piscataway, NJ: IEEE Press, 2009: 319-322.
|
| [5] |
熊华钢, 李峭, 黄永葵.航空电子全双工交换式以太网标准研究(续)[J].航空标准化与质量, 2008(2):20-23. http://d.old.wanfangdata.com.cn/Periodical/hkbzhyzl200802008
XIONG H G, LI Q, HUANG Y K.Research on avionics full duplex switched Ethernet standards (continued)[J].Aviation Standardization and Quality, 2008(2):20-23(in Chinese). http://d.old.wanfangdata.com.cn/Periodical/hkbzhyzl200802008
|
| [6] |
ARINC 664P7-1. Aircraft data network, Part 7: Avionics full duplex switched ethernet (AFDX) network: ARINC 664P7-2005[S].Rio Rancho, NM: ANRIC Standards, 2005.
|
| [7] |
尹伟, 缪万胜, 王念伟, 等.大规模复杂系统的开放式软件架构研究[J].航空电子技术, 2017, 48(2):23-29. http://d.old.wanfangdata.com.cn/Periodical/hkdzjs201702005
YIN W, MIU W S, WANG N W, et al.Open software architecture for large-scale complex systems[J].Avionics Technology, 2017, 48(2):23-29(in Chinese). http://d.old.wanfangdata.com.cn/Periodical/hkdzjs201702005
|
| [8] |
SANG A, LI S.A predictability analysis of network traffic[J].Computer Networks, 2002, 39(4):329-345. https://www.sciencedirect.com/science/article/abs/pii/S1389128601003048
|
| [9] |
LEVIN M, TSAO Y D.On forecasting freeway occupancies and volumes[J].Transportation Research Record Journal of the Transportation Research Board, 1980, 773:47-49. https://trid.trb.org/view/167550
|
| [10] |
张九跃, 焦玉栋.基于RBF神经网络的短时交通流量预测[J].山东交通学院学报, 2008, 16(3):32-36. http://d.old.wanfangdata.com.cn/Periodical/sdjtxyxb200803008
ZHANG J Y, JIAO Y D.Short term traffic flow prediction based on RBF neural network[J].Journal of Shandong Jiaotong University, 2008, 16(3):32-36(in Chinese). http://d.old.wanfangdata.com.cn/Periodical/sdjtxyxb200803008
|
| [11] |
赵岩, 何鹏.网络流量的非线性组合预测模型应用研究[J].计算机仿真, 2012, 29(6):140-144. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jsjfz201206036
ZHAO Y, HE P.Application of nonlinear combination forecasting model for network traffic[J].Computer Simulation, 2012, 29(6):140-144(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jsjfz201206036
|
| [12] |
肖甫, 赵帅帅, 王少辉, 等.基于智能优化的分布式网络流量预测方法[J].北京邮电大学学报, 2015, 38(S1):45-48. http://d.old.wanfangdata.com.cn/Periodical/bjyddx2015z1011
XIAO F, ZHAO S S, WANG S H, et al.Distributed network traffic prediction method based on intelligent optimization[J].Journal of Beijing University of Posts and Telecommunications, 2015, 38(S1):45-48(in Chinese). http://d.old.wanfangdata.com.cn/Periodical/bjyddx2015z1011
|
| [13] |
赵季红, 王明欣, 曲桦, 等.一种基于自适应KLMS的卫星网络流量预测算法[J].北京邮电大学学报, 2018, 41(3):51-55. http://d.old.wanfangdata.com.cn/Periodical/bjyddx201803009
ZHAO J H, WANG M X, QU H, et al.A satellite network traffic prediction algorithm based on adaptive KLMS[J].Journal of Beijing University of Posts and Telecommunications, 2018, 41(3):51-55(in Chinese). http://d.old.wanfangdata.com.cn/Periodical/bjyddx201803009
|
| [14] |
焦文喆, 翟正军, 王国庆.时间触发AFDX调度设计及实时性分析[J].计算机工程, 2016, 42(7):42-48. http://d.old.wanfangdata.com.cn/Periodical/jsjgc201607007
JIAO W Z, ZHAI Z J, WANG G Q.Design and real-time analysis of time-triggered AFDX scheduling[J].Computer Engineering, 2016, 42(7):42-48(in Chinese). http://d.old.wanfangdata.com.cn/Periodical/jsjgc201607007
|
| [15] |
黄婷婷, 余磊.SDAE-LSTM模型在金融时间序列预测中的应用[J].计算机工程与应用, 2019, 55(1):142-148. http://d.old.wanfangdata.com.cn/Periodical/jsjgcyyy201901022
HUANG T T, YU L.Application of SDAE-LSTM model in financial time series forecasting[J].Computer Engineering and Application, 2019, 55(1):142-148(in Chinese). http://d.old.wanfangdata.com.cn/Periodical/jsjgcyyy201901022
|
| [16] |
周瑞, 魏正英, 张育斌, 等.基于LSTM递归神经网络的番茄目标产量时间序列预测[J].节水灌溉, 2018(8):66-70. http://d.old.wanfangdata.com.cn/Periodical/jsgg201808014
ZHOU R, WEI Z Y, ZHANG Y B, et al.Time series forecast of tomato target yield based on LSTM recursive neural network[J].Water-saving Irrigation, 2018(8):66-70(in Chinese). http://d.old.wanfangdata.com.cn/Periodical/jsgg201808014
|
| [17] |
TAMASSELICEAN D, POP P, STEINER W.Timing analysis of rate constrained traffic for the TTEthernet communication protocol[C]//IEEE International Symposium on Real-Time Distributed Computing.Piscataway, NJ: IEEE Press, 2015: 119-126.
|
| [18] |
BENGIO Y, GOODFELLOW I.深度学习[M].北京:人民邮电出版社, 2017.
BENGIO Y, GOODFELLOW I.Deep learning[M].Beijing:Posts and Telecom Press, 2017(in Chinese).
|
| [19] |
张文刚.基于深度学习的交通预测技术及其在通信中的应用研究[D].成都: 西南交通大学, 2018. http://cdmd.cnki.com.cn/Article/CDMD-10613-1018709289.htm
ZHANG W G.Traffic forecasting technology based on in-depth learning and its application in communication[D].Chengdu: Southwest Jiaotong University, 2018(in Chinese). http://cdmd.cnki.com.cn/Article/CDMD-10613-1018709289.htm
|
| [20] |
GERS F, SCHMIDHUBER J, CUMMINS F.Learning to forget:Continual prediction with LSTM[J].Neural Computation, 2000, 12(10):2451-2471. doi: 10.1162/089976600300015015
|
| [21] |
周德新, 王彦翔.AFDX网络分析及带宽分配间隔设定策略[J].科学技术与工程, 2016, 16(9):226-230. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=kxjsygc201609039
ZHOU D X, WANG Y X.AFDX network analysis and bandwidth allocation interval setting strategy[J].Science and Technology and Engineering, 2016, 16(9):226-230(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=kxjsygc201609039
|
| [22] |
LEÓN A P, PIEDRAHITA E M, SALCEDO O.On-off model applications to communication networks aggregated traffic[J].Cuadernos De Derecho Agrario, 2011, 15(30):129-147.
|
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