You are currently viewing a new version of our website. To view the old version click .
Processes
  • Review
  • Open Access

22 July 2023

A Survey on Time-Sensitive Networking Standards and Applications for Intelligent Driving

and
Information Engineering School, Shanghai Maritime University, Shanghai 201306, China
*
Author to whom correspondence should be addressed.
This article belongs to the Special Issue Smart Internet of Things for Industry and Manufacturing Processes

Abstract

Stimulated by the increase in user demands and the development of intelligent driving, the automotive industry is pursuing high-bandwidth techniques, low-cost network deployment and deterministic data transmission. Time-sensitive networking (TSN) based on Ethernet provides a possible solution to these targets, which is arousing extensive attention from both academia and industry. We review TSN-related academic research papers published by major academic publishers and analyze research trends in TSN. This paper provides an up-to-date comprehensive survey of TSN-related standards, from the perspective of the physical layer, data link layer, network layer and protocol test. Then we classify intelligent driving products with TSN characteristics. With the consideration of more of the latest specified TSN protocols, we further analyze the minimum complete set of specifications and give the corresponding demo setup for the realization of TSN on automobiles. Open issues to be solved and trends of TSN are identified and analyzed, followed by possible solutions. Therefore, this paper can be an investigating basis and reference of TSN, especially for the TSN on automotive applications.

1. Introduction

The structure of traditional automobile network is relatively simple, where a controller connects with devices in its domain and different controllers do not interfere with each other. With the increase in user demands on various functionalities, the number of electrical control units (ECUs) of automobiles has gradually increased. Information exchange between ECUs has become more complicated and requires high bandwidth. In addition, with the popularization of the automatic data acquisition system (ADAS) for intelligent driving, more and more sensors, cameras and entertainment systems are being integrated into automobiles, which place higher performance requirements on the certainty, latency and jitter of automobile networks. Ethernet has a simple connection mechanism and protocol operation, which can provide 10 G, even 100 G, bandwidth for data transmission. Compared with traditional solutions, such as controller area network (CAN) [1], local interconnect network (LIN) [2], media-oriented system transport (MOST) [3] and FlexRay [4], Ethernet is a promising solution to in-vehicle networks and is more likely to be dominant. However, the definition of Ethernet fundamentally lacks attributes to guarantee deterministic, low-latency and jitter data transmission for time-sensitive and critical applications. Thereby, new networking techniques need to be studied to further develop Ethernet for automobile networks. In this context, time-sensitive networking (TSN) is proposed to enable real-time and deterministic transmission for critical traffic based on Ethernet hardware.
The TSN family of standards is a tool set that offers reliability, determinism and time synchronization for safety-critical automotive communications over Ethernet links. The TSN standards leverage the previous work conducted within the IEEE 802.1 Working Group on IEEE audio video bridging (AVB). TSN is a set of specifications standardized by the Institute of Electrical and Electronics Engineers (IEEE) 802.1 work group (WG), the predecessor of which is audio video bridging (AVB) [5]. AVB was firstly specified to support the real-time transmission of audio/video (A/V) traffic, which includes synchronization specification, simple resource reservation and scheduling specifications. As more time-sensitive applications emerge, AVB standards are not only used for A/V transmissions but also to manufacture automation, automotive, mobile communication network front haul, etc. [6,7]. Thus, EEE 802.1 WG renames AVB as TSN to better reflect the expanded scope and issues more specifications to improve the real-time capability and reliability of Ethernet. Nowadays, TSN provides various synchronization, resource reservation, queuing and scheduling, control and configuration, certainty, security and safety mechanisms. Updated versions and new specifications are still being developed. In addition to standards, both industry and academia also pay attention to the study of TSN, which are usually in terms of the following fields. Firstly, the time-synchronization designs are investigated, which make network devices synchronized to a reference clock with the accuracy between 1 µs and 10 ns. Secondly, resource-management schemes are designed, which reserve bandwidth for critical time-sensitive traffic with guaranteed latency. To further provide the bounded latency, some queuing and forwarding schemes are investigated, which give priority for critical traffic, while trying to reduce the side effects on general traffic to coexist with them. Thirdly, centralized, distributed, hybrid configuration models and configuration languages are studied to provide static or dynamic control on the synchronization, resource management and scheduling. Finally, security and certainty guaranteed schemes are studied, such as filtering, redundancy provision, link aggregation, etc.
In this paper, we present all related standards on TSN, which not only include those specified by IEEE 802.1 WG but also those specified by the Internet Engineering Task Force (IETF), IEEE 802.3 WG and OPEN Alliance (OA). In addition, we discuss related products, and analyze the demo setup and promising techniques of TSN used for intelligent driving applications. The rest of the paper is organized as follows. Section 2 is the related work. Section 3 presents published and ongoing standards of TSN, which can be used for autonomous driving. Section 4 introduces vehicle TSN products, such as switch, endpoint and protocol stack. Section 5 gives a demo setup for the realization of TSN on a car. Then, open issues and trends of TSN are analyzed in Section 6. Finally, Section 7 concludes this paper. Table 1 summarizes the contribution of our work in comparison to previous relevant surveys.
Table 1. A comparison of contribution between our survey and relevant surveys.

4. TSN-Related Products

Early TSN products were generally used for industrial automation with the realization of main protocols, such as EEE 802.1AS [26], IEEE 802.1Qav [30], and IEEE 802.1Qat [35]. With the development of TSN and autonomous driving, some TSN products for automotive are designed. Active manufacturers in this area mainly include TTTech, Microchip, NXP, Excelfore, Broadcom, Marvell’s, Spirent, etc. In this section, we briefly review some typical TSN products for intelligent driving during recent years.
In terms of TSN switch chip, a NXP product, NXP sja1110, is the first automotive Ethernet switch, which was designed to solve the huge challenges faced by current in-vehicle networks, including scalability, reliability, security, and high-speed traffic engineering. This switch complies with the AVB/TSN synchronization standard. In addition, NXP designed the SJA1105T chip, which is a core of multi-functional product. This switch chip supports a network with standard Ethernet, which not only supports best-effort business but also QoS-required traffic by using TSN for clock synchronization and time-aware shaping. The Microchip Corporation designed a series of Ethernet switches, such as KSZ8565, KSZ8765 and KSZ8842, which support TSN characters, including IEEE 1588 v2 PTP. Broadcom BCM8956X series devices are Broadcom’s fifth-generation fully integrated L2+ multilayer switch solution, which supports AVB protocol stack (IEEE 802.1AS [26] time synchronization and IEEE 802.1Qat [35]). Except for the realization of the basic specifications of AVB, Marvell developed a series of products with more TSN specifications. For example, the switches 88Q5072 and 88Q6113 of Marvell addeds TSN features to achieve the filtering and control of data streams (IEEE 802.1Qci [37]) and frame preemption (IEEE 802.1Qbu [28]). The integrated L3 hardware accelerator allows a gigabit routing throughput of up to 10 Gbps to be achieved without internal processor intervention. To promote big data transmission in the vehicle network, these devices provide efficient sleep/wake functions that support the TC 10 standard, reducing the overall power consumption. Marvell 88Q5050 is an eight-port, high-security automotive gigabit Ethernet switching chip, which has advanced security features to prevent cyber threats, such as DoS attacks. The eight-port Ethernet switch chip has four fixed IEEE 100 BASET1 [22] ports and four configurable ports. The switch chip provides local and remote management functions, and users can easily access and configure the device.
In terms of the TSN protocol stack, Excelfore eAVB/TSN now runs in cameras, video displays, head units and ECUs from numerous vendors. The Excelfore eAVB/TSN has already been ported to automotive-grade operating systems, including Linux, Mentor automotive open system architecture (AUTOSAR) and Green Hills Software INTEGRITY [51]. The Excelfore protocol stacks integrated and optimized for use with the safe and secure INTEGRITY RTOS from Green Hills Software [51], including support for Ethernet AVB/TSN Talker/Listener, DoIP, SOME/IP, and RTP/RTCP (including IEEE 1733) and 802.1AS [26] slave/bridging.
In terms of TSN testing, TTTech designed a combination switch ECU called DESwitch Hermes 3/1 BRR, which is used for evaluating a variety of communication standards, including AVB, TSN and time-triggered Ethernet (SAE AS6802). With these technologies, users can evaluate the convergence of Ethernet control traffic, including security applications and the vehicle backbone architecture. Polelink developed a TSN test tool for automotive Ethernet called the TSN box. This TSN box is a network interface and gateway for TSN network. It was developed based on field programmable gate array (FPGA) technology to serve as a data collection medium for TSN tools, which supports nanosecond timestamps for time synchronization among multiple TSN boxes.
In addition, the TSN box provides rich functional support for AVB and TSN protocols commonly used in automotive Ethernet architectures, which can be used for exploring PTPv2, 802.1ASrev [27] and different TSN shaping algorithms, such as CBS, time-sensitive or asynchronous shaping. Xinertai launched an automotive Ethernet test program based on the proprietary BigTao hardware test platform. Cooperating with Xinerta’s software Renix [52], the Ethernet test program can realize Layer 2–7 traffic test and protocol simulation for automotive Ethernet, support 100/1000 Base-T1 port connectivity test, RFC2889/RFC2544/RFC3918 standard test suite, routing and switching protocol testing, AVB/TSN protocol testing, distributed denial-of-service (DDoS) attack testing, long-term (such as 10 * 24 h) stability and streaming testing, etc. Spirent issued the AUTOSAR conformance test suite pack, which provides different protocol conformance test suites according to the OA test specification. Through this test suite, automotive Ethernet tests can be run on Spirent C1 and C50 devices, which supports testing on clock synchronization and 802.1 Qav [30] scheduling of TSN.
For the vehicle Ethernet PHY chip, it must firstly meet the IEEE 802.3bw or IEEE 802.3bp protocol, and then must pass the AEC-Q 100 standard. The existing semiconductor manufacturers that have launched automotive Ethernet PHY chips include BCM 89610, BCM 89611, BCM 8988X, BCM 89810, BCM 89811 and BCM 89820 of Broadcom, AR 8031 of Artheros, TJA 1100, TJA 1101 and TJA 1102 of NXP. For example, NXP TJA 1101 is based on the IEEE 100 BASE-T1 standard, with the single-port Ethernet PHY transceiver. NXP TJA 1101 meets the needs of automotive applications and supports 100 Mb/s transmission, and its receiving capacity is over 15 m of the unshielded twisted pair. TJA 1100 can achieve the lowest system cost, and meet the strict restrictions on area and heat dissipation of the sensors of the new generation of ECU and ADAS. It complies with AEC-Q 100 level 1, and the original design intention has the smallest package size, the lowest external component overhead and low power consumption.

5. Demo Setup of TSN

To realize basic functions of TSN and provide a deterministic network for autonomous driving, the least complete set of standards to be realized should be considered. The complete set of most TSN products is usually constructed by standards of AVB, i.e., 802.1AS [26], 802.1Qav [30], and 802.1Qat [35], which are mainly used for A/V streams. Here, we further consider some recent TSN specifications for the basic set. Before studying the least complete set, we firstly present the traffic classes and requirements of vehicular applications, which are shown in Table 4.
Table 4. Traffic classes and requirements of vehicular applications.
Safety-relevant devices, such as multiple kinds of sensors, need synchronization with each other to infuse them. In addition, synchronization is the preliminary step of many scheduling and management schemes. Thus, the 802.1AS [26] specification needs to be realized first. To provide deterministic transmission for critical traffic, such as the control comment, bandwidth reservation is needed. On the other hand, the traffic class is finite and fixed, compared with that of industry. Thus, a preferred bandwidth reservation method is pre-allocating the bandwidth for different application traffic instead of 802.1Qat [35] to reduce the signaling overhead and related information storage brought by the stream register of 802.1Qat. Correspondingly, a scheduling method is needed for bridges and end stations to queue and forward frames with different classes. 802.1Qav [30] is preferred for data transmission within a domain. For data transmission among multiple domains, 802.1Qbv [31] is an alternative method. In addition, 802.1CB can provide a baseline for giving redundant paths and supporting robustness. 802.1Qcc [36] can provide corresponding configuration for these protocols. Other specifications can be further realized for a more robust and deterministic network. The basic TSN protocol stack model of the switch of in-vehicle networks is shown in Figure 4, where blue blocks construct a minimum complete set of standards to be realized for a TSN-supported bridge of automotive networks. The end station can be seen as a bridge with a port.
Figure 4. A basic TSN protocol stack model of automobile networks.
For the TSN demo set up, the above functions are expected to be examined and displayed. Here, we give a demo setup for some typical functions, such as that of 802.1AS, 802.1Qbv, and 802.1CB, which is shown in Figure 5.
Figure 5. A demo setup for some typical TSN functions.
As shown in this figure, synchronization is examined by observing whether two A/V traffic generators are synchronized or not. They can be two AVB cameras recording the same view. In Display 1, it shows the views of two cameras, respectively. When they are synchronized, the displayed views of the two cameras are the same. This is an intuitive show. More accurately, it can be tested by using time-record software. Two cameras photograph the software with the time display and transmit them to DCU 1. Then, we can see whether the transmitted pictures with time are the same or not. 802.1Qbv [31] is checked by using three traffic generators, i.e., A/V traffic, best-effort traffic and control traffic. With the interfering traffic (BE traffic and A/V traffic), the delay and jitter performance of control traffic can be observed, which should not be affected by the interfering traffic and have guaranteed latency and low jitter based on Qbv. For the 802.1CB demo, redundant routing is used for critical traffic. The robustness of the traffic transmission can be observed by allowing routing congestion with abundant traffic.
We simulated the time-synchronization effect of 802.1AS [26] and the traffic-scheduling performance of 802.1Qbv [31]. The simulation environment developed here is based on FPGA, and the PHY chip is Realtek RTL8201CP, which has a clock frequency of 25 MHz at 100 Mbps, i.e., the clock accuracy is 40 ns. The corresponding waveforms were obtained and analyzed experimentally.
As shown in Figure 6, the vertical coordinate time offset represents the time deviation between nodes measured at each time in μ s, and the horizontal coordinate time represents the time-synchronization interval, which is 1 s. After a short period of jitter at the beginning of the time synchronization, the time deviation between nodes tends to converge; the final value of this time-synchronous convergence converges to 14.5 μ s. The simulation experimental results show the effectiveness of the time synchronization, which shows that AS is feasible in the demo setup.
Figure 6. Time offset between two nodes.
In Figure 7, the vertical axis end-to-end latency represents the total time it takes for a data packet to be sent from the sender to the receiver, measured in microseconds ( μ s). The horizontal coordinate sampling times indicates the number of times the data are sampled at the same time interval. The impact of enabling the time-synchronization feature on the traffic-scheduling performance of the TAS algorithm is verified by comparing with and without enabling time synchronization, and the results show that the end-to-end delay of traffic is reduced by an average of 80 μ s when time synchronization is enabled. In addition, simulation experiments show that Qbv achieves end-to-end low latency performance under time synchronization, which also validates the effectiveness and feasibility of the demo setup.
Figure 7. End-to-end delay of traffic transmission.

7. Conclusions

In this paper, we presented an in-depth survey of time-sensitive networking (TSN) for intelligent driving. We introduced TSN-related standards specified by the Institute of Electrical and Electronics Engineers (IEEE) 802.3 work group (WG), IEEE 802.1 WG, Internet Engineering Task Force (IETF) and OPEN Alliance (OA) from the physical layer to the network layer to enable Ethernet to provide deterministic, low-latency and high bandwidth data transmission for emerging applications brought by intelligent driving. Furthermore, we revealed corresponding automotive products based on these TSN specifications. In addition, we analyzed a minimum set of specifications that should be considered to realize TSN functions for automotive applications, based on which we presented a demo setup. Based on our survey, we concluded the existing techniques of TSN, and identified corresponding solutions and proposed potential solutions to address these issues. We also gave some promising techniques and ongoing standards of TSN, including new designs of synchronization, configuration, robustness, resource allocation and the TSN based on the wireless channel, followed by a discussion of its feasibility for automotive applications. With the aid of this survey, researchers can obtain a quick understanding of the contents, progress and challenges of TSN on automotive networks. Furthermore, developers of TSN can draw lessons from solutions provided in this paper both in term of theory and practice.

Author Contributions

Conceptualization, Y.X.; Writing—original draft, Y.X.; Writing—review and editing, Y.X. and J.H. All authors have read and agreed to the published version of the manuscript.

Funding

This work was partially supported by the National Natural Science Foundation of China (62271303); The Innovation Program of Shanghai Municipal Education Commission of China (2021-01-07-00-10-E00121); The Natural Science Foundation of Shanghai (20ZR1423200).

Data Availability Statement

Data sharing not applicable No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare that they have no known competing financial interest or personal relationship that could have appeared to influence the work reported in this paper.

References

  1. Can Specifications. Bosch Std. 1991. Available online: https://www.kvaser.com/software/7330130980914/V1/can2spec.pdf (accessed on 15 June 2023).
  2. Specification of Lin Interface. AUTOSAR Std. 2017. Available online: https://www.autosar.org/fileadmin/LINInterface.pdf (accessed on 15 June 2023).
  3. Most Specification. MOST Std. 2006. Available online: https://www.mostcooperation.com/publications//mostspecificationpdf/ (accessed on 15 June 2023).
  4. Consortium, F. Flexray communicationssystem-protocol specification. Version 2005, 2, 198–207. [Google Scholar]
  5. Teener, M.D.J.; Fredette, A.N.; Boiger, C.; Klein, P.; Gunther, C.; Olsen, D.; Stanton, K. Heterogeneous networks for audio and video: Using ieee 802.1 audio video bridging. Proc. IEEE 2013, 101, 2339–2354. [Google Scholar] [CrossRef]
  6. Renesas, J.T. In Requirements for Automotive AVB System Profiles; Technol Report; AVnu Alliance: Beaverton, OR, USA; 2011. Available online: https://avnu.org/wp-content/uploads/2014/05/Contributed-Automotive-Whitepaper_April-2011.pdf (accessed on 15 June 2023).
  7. Bruckner, D.; Stanica, M.-P.; Blair, R.; Schriegel, S.; Kehrer, S.; Seewald, M.; Sauter, T. An introduction to opc ua tsn for industrial communication systems. Proc. IEEE 2019, 107, 1121–1131. [Google Scholar] [CrossRef]
  8. Bello, L.L.; Mariani, R.; Mubeen, S.; Saponara, S. Recent advances and trends in on-board embedded and networked automotive systems. IEEE Trans. Ind. Inform. 2019, 15, 1038–1051. [Google Scholar] [CrossRef]
  9. Sabry, A.; Omar, A.; Hammad, M.; Abdelbaki, N. AVB/TSN protocols in automotive networking. In Proceedings of the 2020 15th International Conference on Computer Engineering and Systems (ICCES), Cairo, Egypt, 15–16 December 2020; pp. 1–7. [Google Scholar]
  10. Deng, L.; Xie, G.; Liu, H.; Han, Y.; Li, R.; Li, K. A Survey of Real-Time Ethernet Modeling and Design Methodologies: From AVB to TSN. ACM Comput. Surv. 2022, 55, 31. [Google Scholar] [CrossRef]
  11. Bello, L.L.; Daneshtalab, M.; Mubeen, S.; Saponara, S.; Ashjaei, M.; Patti, G. Time-Sensitive Networking in automotive embedded systems: State of the art and research opportunities. J. Syst. Archit. 2021, 117, 102137. [Google Scholar]
  12. Peng, Y.; Shi, B.; Jiang, T.; Tu, X.; Xu, D.; Hua, K. A Survey on In-vehicle Time Sensitive Networking. IEEE Internet Things J. 2023; early access. [Google Scholar]
  13. Bello, L.L.; Steiner, W. A perspective on IEEE time-sensitive networking for industrial communication and automation systems. Proc. IEEE 2019, 107, 1094–1120. [Google Scholar] [CrossRef]
  14. Nasrallah, A.; Thyagaturu, A.S.; Alharbi, Z.; Wang, C.; Shao, X.; Reisslein, M.; ElBakoury, H. Ultra-Low Latency (ULL) Networks: The IEEE TSN and IETF DetNet Standards and Related 5G ULL Research. IEEE Commun. Surv. Tutor. 2019, 21, 88–145. [Google Scholar] [CrossRef]
  15. Finn, N. Introduction to time-sensitive networking. IEEE Commun. Stand. Mag. 2018, 2, 22–28. [Google Scholar] [CrossRef]
  16. Messenger, J.L. Time-sensitive networking: An introduction. IEEE Commun. Stand. Mag. 2018, 2, 29–33. [Google Scholar] [CrossRef]
  17. Cavalcanti, D.; Perez-Ramirez, J.; Rashid, M.M.; Fang, J.; Galeev, M.; Stanton, K.B. Extending accurate time distribution and timeliness capabilities over the air to enable future wireless industrial automation systems. Proc. IEEE 2019, 107, 1132–1152. [Google Scholar] [CrossRef]
  18. Kang, Y.; Lee, S.; Gwak, S.; Kim, T.; An, D. Time-sensitive networking technologies for industrial automation in wireless communication systems. Energies 2021, 14, 4497. [Google Scholar] [CrossRef]
  19. Samii, S.; Zinner, H. Level 5 by layer 2: Time-sensitive networking for autonomous vehicles. IEEE Commun. Stand. Mag. 2018, 2, 62–68. [Google Scholar] [CrossRef]
  20. Leonardi, L.; Bello, L.L.; Patti, G. Bandwidth partitioning for Time-Sensitive Networking flows in automotive communications. IEEE Commun. Lett. 2021, 25, 3258–3261. [Google Scholar] [CrossRef]
  21. IEEE 802.1. Time-Sensitive Networking (TSN) Task. Available online: https://1.ieee802.org/tsn/ (accessed on 15 June 2023).
  22. IEEE P802.3bw/D3.3; IEEE Approved Draft Standard for Ethernet Amendment: Physical Layer Specifications and Management Parameters for 100 Mb/s Operation over a Single Balanced Twisted Pair Cable (100BASE-T1). IEEE Std.: Piscataway, NJ, USA, 2015.
  23. IEEE Std 802.3cg; IEEE Draft Standard for Ethernet Amendment 5: Physical Layer Specifications and Management Parameters for 10 Mb/s Operation and Associated Power Delivery over a Single Balanced Pair of Conductors. IEEE Std.: Piscataway, NJ, USA, 2019.
  24. IEEE Std 802.3ch; IEEE Standard for Ethernet–Amendment 8: Physical Layer Specifications and Management Parameters for 2.5 Gb/s, 5 Gb/s, and 10 Gb/s Automotive Electrical Ethernet. IEEE Std.: Piscataway, NJ, USA, 2020.
  25. IEEE 802.3 Working Group. Available online: https://www.ieee802.org/3/ (accessed on 15 April 2023).
  26. 802.1AS-2020; IEEE Standard for Local and Metropolitan Area Networks–Timing and Synchronization for Time-Sensitive Applications. IEEE Std.: Piscataway, NJ, USA, 2020.
  27. P802.1AS-Rev/D8.3; IEEE Draft Standard for Local and Metropolitan Area Networks-Timing and Synchronization for Time-Sensitive Applications. IEEE Std.: Piscataway, NJ, USA, 2019; pp. 1–516.
  28. 802.1Qbu-2016; IEEE Standard for Local and Metropolitan Area Networks–Bridges and Bridged Networks–Amendment 26: Frame Preemption. IEEE Std.: Piscataway, NJ, USA, 2016; pp. 1–52. [CrossRef]
  29. 802.1br-2012; IEEE Standard for Local and Metropolitan Area Networks–Virtual Bridged Local Area Networks–Bridge Port Extension. IEEE Std.: Piscataway, NJ, USA, 2012; pp. 1–135. [CrossRef]
  30. 802.1Qav-2009; IEEE Standard for Local and Metropolitan Area Networks–Virtual Bridged Local Area Networks Amendment 12: Forwarding and Queuing Enhancements for Time-Sensitive Streams. IEEE Std.: Piscataway, NJ, USA, 2009; pp. 1–72.
  31. 802.1Qbv-2015; IEEE Standard for Local and Metropolitan Area Networks–Bridges and Bridged Networks-Amendment 25: Enhancements for Scheduled Traffic. IEEE Std.: Piscataway, NJ, USA, 2015; pp. 1–57. [CrossRef]
  32. 802.1Qch-2017; IEEE Standard for Local and Metropolitan Area Networks–Bridges and Bridged Networks–Amendment 29: Cyclic Queuing and Forwarding. IEEE Std.: Piscataway, NJ, USA, 2017; pp. 1–30. [CrossRef]
  33. 802.1Qcr-2020; IEEE Standard for Local and Metropolitan Area Networks–Bridges and Bridged Networks-Amendment 34: Asynchronous Traffic Shaping. IEEE Std.: Piscataway, NJ, USA, 2020; pp. 1–151. [CrossRef]
  34. 802.1Qca-2015; IEEE Standard for Local and metropolitan area networks—Bridges and Bridged Networks-Amendment 24: Path Control and Reservation. IEEE Std.: Piscataway, NJ, USA, 2015; pp. 1–120. [CrossRef]
  35. 802.1Qat-2010; IEEE Standard for Local and metropolitan area networks–Virtual Bridged Local Area Networks Amendment 14: Stream Reservation Protocol (SRP). IEEE Std.: Piscataway, NJ, USA, 2010; pp. 1–119. [CrossRef]
  36. 802.1Qcc-2018; IEEE Standard for Local and Metropolitan Area Networks–Bridges and Bridged Networks–Amendment 31: Stream Reservation Protocol (srp) Enhancements and Performance Improvements. IEEE Std.: Piscataway, NJ, USA, 2018; pp. 1–208.
  37. 802.1Qci-2017; IEEE Standard for Local and metropolitan area networks–Bridges and Bridged Networks–Amendment 28: Per-Stream Filtering and Policing. IEEE Std.: Piscataway, NJ, USA, 2017. [CrossRef]
  38. 802.1CB-2017; IEEE Standard for Local and Metropolitan Area Networks–Frame Replication and Elimination for Reliability. IEEE Std.: Piscataway, NJ, USA, 2017.
  39. IEEE 1588; IEEE Draft Standard Profile for Use of IEEE 1588 Precision Time Protocol in Power System Applications. IEEE Std.: Piscataway, NJ, USA, 2015; pp. 1–49.
  40. Chen, R.; Zhang, Y.; Cao, C.; Zhao, Y.; Li, B.; Zhang, J.; Gu, W. Clock synchronization in t-mpls network via ptp (ieee 1588 v2). In Proceedings of the 2009 Asia Communications and Photonics Conference and Exhibition (ACP), Shanghai, China, 13–16 November 2011; pp. 1–8. [Google Scholar]
  41. Antonova, G.S.; Apostolov, A.; Amold, D.; Bedrosian, P.S. Standard profile for use of ieee std 1588-2008 precision time protocol (ptp) in power system applications. In Proceedings of the 2013 66th Annual Conference for Protective Relay Engineers, College Station, TX, USA, 8–11 April 2013; pp. 322–336. [Google Scholar]
  42. 802.1AX-2014; IEEE Standard for Local and Metropolitan Area Networks–Link Aggregation. IEEE Std.: Piscataway, NJ, USA, 2014.
  43. 802.1Q-2018. IEEE Standard for Local and Metropolitan Area Network–Bridges and Bridged Networks. IEEE Std.: Piscataway, NJ, USA, 2018.
  44. Finn, N.; Thubert, P.; Varga, B.; Farkas, J. Deterministic Networking Architecture. RFC 8655. 2019. Available online: https://www.rfc-editor.org/info/rfc8655 (accessed on 15 June 2023). [CrossRef]
  45. Varga, B.; Farkas, J.; Berger, L.; Malis, A.G.; Bryant, S. Deterministic Networking (DetNet) Data Plane Framework. RFC 8938. 2020. Available online: https://www.rfc-editor.org/info/rfc8938 (accessed on 15 June 2023). [CrossRef]
  46. Geng, X.; Ryoo, Y.; Fedyk, D.; Rahman, R.; Li, Z. Deterministic Networking (DetNet) YANG Model. Internet-Draft draft-ietf-detnet-yang-17, Internet Engineering Task Force. 2022; work in progress. [Google Scholar]
  47. Varga, B.; Farkas, J.; Malis, A.G.; Bryant, S. Deterministic Networking (DetNet) Data Plane: IP over IEEE 802.1 Time-Sensitive Networking (TSN). RFC 9023. 2021. Available online: https://www.rfc-editor.org/info/rfc9023 (accessed on 15 June 2023). [CrossRef]
  48. Varga, B.; Farkas, J.; Malis, A.G.; Bryant, S. Deterministic Networking (DetNet) Data Plane: MPLS over IEEE 802.1 Time-Sensitive Networking (TSN). RFC 9037. 2021. Available online: https://www.rfc-editor.org/info/rfc9037 (accessed on 15 June 2023). [CrossRef]
  49. 802.1CBdb-2021; IEEE Standard for Local and Metropolitan Area Networks–Frame Replication and Elimination for Reliability Amendment 2: Extended Stream Identification Functions. IEEE Std.: Piscataway, NJ, USA, 2021; pp. 1–90. [CrossRef]
  50. OPEN TC11; TC 11 Switch Semiconductor Test Specification. OPEN Alliance Std.: Irvine, CA, USA, 2018. Available online: https://www.opensig.org/tech-committees/tc11/ (accessed on 15 June 2023).
  51. Green Hills Software (n.d.). INTEGRITY Real Time Operating System (RTOS). Available online: https://ghs.com/products/rtos/integrity.html (accessed on 15 June 2023).
  52. Xinerta. Renix Software. Available online: https://xinertel.com/NewsInfoSearch?searchKey=Renix (accessed on 15 June 2023).
  53. Ghosal, A.; Halder, S.; Conti, M. Secure over-the-air software update for connected vehicles. Comput. Netw. 2022, 218, 109394. [Google Scholar] [CrossRef]
  54. Du, J.L.; Herlich, M. Software-defined Networking for Real-time Ethernet. In Proceedings of the ICINCO (2), Lisbon, Portugal, 29–31 July 2016; pp. 584–589. [Google Scholar]
  55. Ehrlich, M.; Krummacker, D.; Fischer, C.; Guillaume, R.; Olaya, S.S.P.; Frimpong, A.; de Meer, H.; Wollschlaeger, M.; Schotten, H.D.; Jasperneite, J. Software-defined networking as an enabler for future industrial network management. In Proceedings of the 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), Torino, Italy, 4–7 September 2018; Volume 1, pp. 1109–1112. [Google Scholar]
  56. Schriegel, S.; Kobzan, T.; Jasperneite, J. Investigation on a distributed SDN control plane architecture for heterogeneous time sensitive networks. In Proceedings of the 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS), Imperia, Italy, 13–15 June 2018; pp. 1–10. [Google Scholar]
  57. P802.1DG; TSN Profile for Automotive In-Vehicle Ethernet Communications. IEEE Std.: Piscataway, NJ, USA, 2023. Available online: https://1.ieee802.org/tsn/802-1dg/ (accessed on 15 June 2023).
  58. Häckel, T.; Meyer, P.; Korf, F.; Schmidt, T.C. SDN4CoRE: A simulation model for software-defined networking for communication over real-time ethernet. arXiv 2019, arXiv:1908.09649. [Google Scholar]
  59. Boudec, J. A Theory of Traffic Regulators for Deterministic Networks with Application to Interleaved Regulators. IEEE/ACM Trans. Netw. 2018, 26, 2721–2733. [Google Scholar] [CrossRef]
  60. P802.1Qdd; Resource Allocation Protocol. IEEE Std.: Piscataway, NJ, USA, 2023. Available online: https://1.ieee802.org/tsn/802-1qdd/ (accessed on 15 June 2023).
  61. P802.1Qdj; Configuration Enhancements for Time-Sensitive Networking. IEEE Std.: Piscataway, NJ, USA, 2023. Available online: https://1.ieee802.org/tsn/802-1qdj/ (accessed on 15 June 2023).
  62. P802.1ASdm; Hot Standby. IEEE Std.: Piscataway, NJ, USA, 2023. Available online: https://1.ieee802.org/tsn/802-1asdm/ (accessed on 15 June 2023).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Multiple requests from the same IP address are counted as one view.