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面向工业无线网络的动态TDMA系统设计与实现

徐川 曾日辉 邢媛 邓炳光 赵国锋

徐川, 曾日辉, 邢媛, 邓炳光, 赵国锋. 面向工业无线网络的动态TDMA系统设计与实现. 自动化学报, 2020, 41(x): 1−11 doi: 10.16383/j.aas.c190797
引用本文: 徐川, 曾日辉, 邢媛, 邓炳光, 赵国锋. 面向工业无线网络的动态TDMA系统设计与实现. 自动化学报, 2020, 41(x): 1−11 doi: 10.16383/j.aas.c190797
Xu Chuang, Zeng Ri-Hui, Xing Yuan, Deng Bing-Guang, Zhao Guo-Feng. Design and implementation of dynamic tdma system for industrial wireless networks. Acta Automatica Sinica, 2020, 41(x): 1−11 doi: 10.16383/j.aas.c190797
Citation: Xu Chuang, Zeng Ri-Hui, Xing Yuan, Deng Bing-Guang, Zhao Guo-Feng. Design and implementation of dynamic tdma system for industrial wireless networks. Acta Automatica Sinica, 2020, 41(x): 1−11 doi: 10.16383/j.aas.c190797

面向工业无线网络的动态TDMA系统设计与实现

doi: 10.16383/j.aas.c190797
基金项目: 国家重点研发计划项目(2018YFB1800301, 2018YFB1800304), 国家科技重大专项(2018ZX03001016), 重庆市研究生科研创新项目(CYB19176, BYJS201905) 资助
详细信息
    作者简介:

    徐川 重庆邮电大学通信与信息工程学院教授. 主要研究方向为工业互联网, 软件定义网络, 网络测量, 天地一体化网络. 本文通信作者. E-mail: xuchuan@cqupt.edu.cn

    曾日辉:重庆邮电大学通信与信息工程学院硕士研究生. 主要研究方向为工业互联网, 软件定义网络, 时间敏感网络. E-mail: zrh_113113@126.com

    邢媛:重庆邮电大学通信与信息工程学院博士生. 主要研究方向为工业物联网, 时间敏感网络. E-mail: xingystudy@foxmail.com

    邓炳光:重庆邮电大学通信与信息工程学院副教授. 主要研究方向为通信网与测试技术, 仪器科学与技术. E-mail: dengbg@cqupt.edu.cn

    赵国锋:重庆邮电大学通信与信息工程学院教授. 主要研究方向为工业互联网, 天地一体化网络, 网络测量. E-mail: zhaofg@cqupt.edu.cn

Design and Implementation of Dynamic Tdma System for Industrial Wireless Networks

Funds: Supported by National Key Research and Development Project of China (2018YFB1800301, 2018YFB1800304), National Science and Technology Major Project(2018ZX03001016), the Chongqing Postgraduate Research and Innovation Project (CYB19176, BYJS201905)
  • 摘要: 随着工业4.0的发展, 不同种类的新型工业应用被部署到工厂中, 这对现有工业无线技术提出了实时性和高速率的要求. 为了同时满足这两种需求, 本文在支持高速率的IEEE802.11的基础上, 提出了基于软件定义的动态TDMA无线接入系统. 首先, 为了提供时延有界的传输服务, 设计并实现了基于MAC层的动态TDMA接入机制. 然后, 为了满足工业无线网络中的动态变化的带宽需求, 考虑设备数据量的动态变化, 在SDN控制器上通过基于最小二乘法的线性回归算法预测设备时隙需求, 再将动态时隙分配问题转化为优化问题以最大化网络中所有设备动态时隙需求. 最后, 通过仿真对比TDMA时隙分配算法的性能, 并在实际网络环境中开展系统部署与测试. 结果表明, 相对于其他TDMA接入机制, 动态TDMA机制在保障时延有界的同时能有效提升传输性能.
  • 图  1  工业物联网场景图

    Fig.  1  A typic Industrial wireless Internet of Things.

    图  2  动态TDMA信道接入方式

    Fig.  2  Dynamic TDMA channel access method

    图  3  DTS系统结构图

    Fig.  3  The architecture of DTS system

    图  4  INFO_FEEDBACK帧的结构

    Fig.  4  INFO_FEEDBACK frame structure

    图  5  控制器原理图

    Fig.  5  The schematic of Controller

    图  6  AP原理图

    Fig.  6  The schematic of AP

    图  7  用户设备原理图

    Fig.  7  The Schematic of Device

    图  8  (a) 周期性数据平均时延 (b) 多媒体数据平均时延 (c) 混合数据平均时延

    Fig.  8  (a) Periodic data average delay (b) Multimedia data average delay (c) Mixed data average delay

    图  9  (a) 周期性数据吞吐量 (b) 多媒体数据吞吐量(c) 混合数据吞吐量

    Fig.  9  (a) Periodic data throughput (b) Multimedia data throughput (c) Mixed data throughput

    图  10  测试环境逻辑示意图

    Fig.  10  Test environment logical topology

    图  11  (a) 周期性数据平均时延 (b) 多媒体数据平均时延

    Fig.  11  (a) Periodic data average delay (b) Multimedia data average delay

    图  12  (a) 网络总吞吐量 (b) 周期性数据吞吐量 (c) 多媒体数据吞吐量

    Fig.  12  (a) Total data throughput (b) Periodic data throughput (c) Multimedia data throughput

    表  1  测试硬件设备以及参数

    Table  1  Testing hardware devices and parameters

    设备名称设备型号数目CPU内存网卡操作系统
    控制器台式机1I5-7300四核16GAR9580Windows7
    APWNDR43001QCA9553128MBAR9580OpenWRT
    多媒体设备台式机4E7200双核2GAR9280Ubuntu14
    周期性数据设备WNDR380012AR7161128MBAR9220OpenWRT
    下载: 导出CSV

    表  2  数据帧参数设置

    Table  2  Data frame parameter

    数据类型帧长 (Byte)平均发包数目(个/秒)
    周期性数据260125
    多媒体数据860~1060250
    移动端数据550Random (250)
    下载: 导出CSV
  • [1] Vitturi S, Zunino C, Sauter T. Industrial communication systems and their future challenges: next-generation ethernet, IIoT, and 5G. Proceedings of the IEEE, 2019, 107(6): 944−961 doi: 10.1109/JPROC.2019.2913443
    [2] 王飞跃, 张军, 张俊, 王晓. 工业智联网: 基本概念、关键技术与核心应用. 自动化学报, 2018, 44(09): 1606−1617

    Wang Fei-Yue, Zhang Jun, Zhang Jun, Wang Xiao. Industrial Internet of Minds: Concept, Technology and Application. Acta Automatica Sinica, 2018, 44(09): 1606−1617
    [3] Boyes H, Hallaq B, Cunningham J, Watson T. The industrial internet of things (IIoT): an analysis framework. Computers in Industry, 2018, 101: 1−12 doi: 10.1016/j.compind.2018.04.015
    [4] Bello L L, Steiner W. A perspective on IEEE time-sensitive networking for industrial communication and automation systems. Proceedings of the IEEE, 2019, 107(6): 1094−1120 doi: 10.1109/JPROC.2019.2905334
    [5] Jin X, Xia C, Guan N, Xu C, Li D, Zeng P. Real-time scheduling of massive data in time sensitive networks with a limited number of schedule entries. IEEE Access, 2020, 8: 6751−6767 doi: 10.1109/ACCESS.2020.2964690
    [6] 黄韬, 汪硕, 黄玉栋等. 确定性网络研究综述. 通信学报, 2019, 40(06): 160−176

    Huang Tao, Wang Shuo, Huang Yu-Dong, et al. Survey of the deterministic network. Journal on Communications, 2019, 40(06): 160−176
    [7] Liu Y, Kashef M, Lee K B, Benmohamed L, Candell R. Wireless network design for emerging IIoT applications: reference framework and use cases. Proceedings of the IEEE, 2019, 107(6): 1166−1192 doi: 10.1109/JPROC.2019.2905423
    [8] Yousefi H H, Kavian Y S, Mahmoudi A. A markov model for investigating the impact of IEEE802.15. 4 MAC layer parameters and number of clusters on the performance of wireless sensor networks. Wireless Networks, 2019, 25: 4415−4430
    [9] Papadopoulos G Z, Matsui T, Thubert P, Texier G Watteyne T, Montavont N. Leapfrog collaboration: Toward determinism and predictability in industrial-IoT applications. In: Proceedings of 2017 IEEE International Conference on Communications (ICC), Paris, France: IEEE, 2017.1−6
    [10] Koutsiamanis R A, Papadopoulos G Z, Fafoutis X, Julian M, Fiore D, Thubert P, Montavont N. From best effort to deterministic packet delivery for wireless industrial IoT networks. IEEE Transactions on Industrial Informatics, 2018, 14(10): 4468−4480 doi: 10.1109/TII.2018.2856884
    [11] Prinz F, Schoeffler M, Lechler A, Verl A W. Dynamic real-time orchestration of I4.0 components based on time-sensitive networking. Procedia CIRP, 2018, 72: 910−915 doi: 10.1016/j.procir.2018.03.174
    [12] Messenger J L. Time-sensitive networking: an introduction. IEEE Communications Standards Magazine, 2018, 2(2): 29−33 doi: 10.1109/MCOMSTD.2018.1700047
    [13] Nasrallah A, Thyagaturu A S, Alharbi Z, Wang C, Shao X, Reisslein M, ElBakoury H. Ultra-low latency networks: The IEEE TSN and IETF DetNet standards and related 5G ULL research. IEEE Communications Surveys & Tutorials, 2018, 21(1): 88−145
    [14] Xia N, Chen H H, Yang C S. Radio resource management in machine-to-machine communications—a survey. IEEE Communications Surveys & Tutorials, 2017, 20(1): 791−828
    [15] Genc E, Del Carpio L F. Wi-Fi QoS enhancements for Downlink Operations in industrial automation using TSN. In: Proceedings of 2019 15th IEEE International Workshop on Factory Communication Systems (WFCS), Sundsvall, Sweden: IEEE, 2019.1−6
    [16] Cena G, Scanzio S, Valenzano A. Improving effectiveness of seamless redundancy in real industrial wi-fi networks. IEEE Transactions on Industrial Informatics, 2017, 14(5): 2095−2107
    [17] Wei Y H, Leng Q, Han S, Mok A K, Zhang W, Tomizuka M. RT-WiFi: real-time high-speed communication protocol for wireless cyber-physical control applications. In: Proceedings of 2013 IEEE 34th Real-Time Systems Symposium, Vancouver, Canada: IEEE, 2013.140−149
    [18] Cheng Y, Yang D, Zhou H. Det-wifi: a multihop tdma mac implementation for industrial deterministic applications based on commodity 802.11 hardware. Wireless Communications and Mobile Computing, 2017, 2017: 1−10
    [19] Amodu O A, Othman M. A survey of hybrid MAC protocols for machine-to-machine communications. Telecommunication Systems, 2018, 69(1): 141−165 doi: 10.1007/s11235-018-0434-4
    [20] Shahin N, Ali R, Kim Y T. Hybrid slotted-csma/ca-tdma for efficient massive registration of iot devices. IEEE Access, 2018, 6: 18366−18382 doi: 10.1109/ACCESS.2018.2815990
    [21] Shoaei A D, Derakhshani M, Parsaeefard S, LeNgoc T. Learning-based hybrid TDMA-CSMA MAC protocol for virtualized 802.11 WLANs. In: Proceedings of 2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), HongKong, China: IEEE, 2015.1861−1866
    [22] Cruces C, Torrego R, Arriola A, Val I. Deterministic hybrid architecture with time sensitive network and wireless capabilities. In: Proceedings of 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), Turin, Italy, IEEE, 2018.1119−1122
    [23] Adame T, Carrascosa M, Bellalta B. Time-sensitive networking in IEEE 802.11 be: on the way to low-latency WiFi 7. Computer Science, 2019: 1912
    [24] Yu M, Rexford J, Freedman M J, Wang J. Scalable flow-based networking with difane. ACM SIGCOMM Computer Communication Review, 2011, 41(4): 351−362
    [25] Xu C, Jin W, Wang X H, Zhao G F, Yu S. MC-VAP: a multi-connection virtual access point for high performance software-defined wireless networks. Journal of network and computer applications, 2018, 122: 88−98 doi: 10.1016/j.jnca.2018.08.009
    [26] Sood K, Yu S, Xiang Y. Software-defined wireless networking opportunities and challenges for internet-of-things: a review. IEEE Internet of Things Journal, 2015, 3(4): 453−463
    [27] McKeown N, Anderson T, Balakrishnan H, Parulkar G, Peterson L, Rexford J. Openflow: enabling innovation in campus networks. ACM SIGCOMM Computer Communication Review, 2008, 38(2): 69−74 doi: 10.1145/1355734.1355746
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  • 收稿日期:  2019-11-20
  • 录用日期:  2020-06-19

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