301 research outputs found
Time Synchronization for 5G and TSN Integrated Networking
Emerging industrial applications involving robotic collaborative operations
and mobile robots require a more reliable and precise wireless network for
deterministic data transmission. To meet this demand, the 3rd Generation
Partnership Project (3GPP) is promoting the integration of 5th Generation
Mobile Communication Technology (5G) and Time-Sensitive Networking (TSN). Time
synchronization is essential for deterministic data transmission. Based on the
3GPP's vision of the 5G and TSN integrated networking with interoperability, we
improve the time synchronization of TSN to conquer the multi-gNB competition,
re-transmission, and mobility problems for the integrated 5G time
synchronization. We implemented the improvement mechanisms and systematically
validated the performance of 5G+TSN time synchronization. Based on the
simulation in 500m x 500m industrial environments, the improved time
synchronization achieved a precision of 1 microsecond with interoperability
between 5G nodes and TSN nodes
Supporting time-sensitive and best-effort traffic on a common metro infrastructure
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Considerable research and standardization efforts are being made to support time-sensitive traffic, e.g., generated by applications like Industry 4.0 and 5G fronthaul, on packet networks. This letter focuses on analyzing the impact of conveying time-sensitive traffic in operators’ networks when such traffic is mixed with best-effort traffic. Extensions to a continuous queue model are proposed to evaluate two different Ethernet technologies, synchronous and asynchronous, supporting time-sensitive flows in terms of their influence on the performance of best-effort traffic. Results highlight pros and cons of those technologies to protect best-effort performance.The research leading to these results has received funding from the European Commission for the H2020-ICT-2016- 2 METRO-HAUL project (G.A. 761727), from the AEI/FEDER TWINS project (TEC2017-90097-R), and from the Catalan Institution for Research and Advanced Studies (ICREA).Peer ReviewedPostprint (author's final draft
TSN-FlexTest: Flexible TSN Measurement Testbed (Extended Version)
Robust, reliable, and deterministic networks are essential for a variety of
applications. In order to provide guaranteed communication network services,
Time-Sensitive Networking (TSN) unites a set of standards for
time-synchronization, flow control, enhanced reliability, and management. We
design the TSN-FlexTest testbed with generic commodity hardware and open-source
software components to enable flexible TSN measurements. We have conducted
extensive measurements to validate the TSN-FlexTest testbed and to examine TSN
characteristics. The measurements provide insights into the effects of TSN
configurations, such as increasing the number of synchronization messages for
the Precision Time Protocol, indicating that a measurement accuracy of 15 ns
can be achieved. The TSN measurements included extensive evaluations of the
Time-aware Shaper (TAS) for sets of Tactile Internet (TI) packet traffic
streams. The measurements elucidate the effects of different scheduling and
shaping approaches, while revealing the need for pervasive network control that
synchronizes the sending nodes with the network switches. We present the first
measurements of distributed TAS with synchronized senders on a commodity
hardware testbed, demonstrating the same Quality-of-Service as with dedicated
wires for high-priority TI streams despite a 200% over-saturation cross traffic
load. The testbed is provided as an open-source project to facilitate future
TSN research.Comment: 30 pages, 18 figures, 6 tables, IEEE TNSM, in print, 2024. Shorter
version in print in IEEE Trans. on Network and Service Management (see
related DOI below
5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0
This work has been partially funded by the H2020 project 5G-CLARITY (Grant No. 871428) and the Spanish national project TRUE-5G (PID2019-108713RB-C53).Fifth Generation (5G) is expected to meet stringent performance network requisites of
the Industry 4.0. Moreover, its built-in network slicing capabilities allow for the support of the
traffic heterogeneity in Industry 4.0 over the same physical network infrastructure. However, 5G
network slicing capabilities might not be enough in terms of degree of isolation for many private
5G networks use cases, such as multi-tenancy in Industry 4.0. In this vein, infrastructure network
slicing, which refers to the use of dedicated and well isolated resources for each network slice at every
network domain, fits the necessities of those use cases. In this article, we evaluate the effectiveness of
infrastructure slicing to provide isolation among production lines (PLs) in an industrial private 5G
network. To that end, we develop a queuing theory-based model to estimate the end-to-end (E2E)
mean packet delay of the infrastructure slices. Then, we use this model to compare the E2E mean
delay for two configurations, i.e., dedicated infrastructure slices with segregated resources for each
PL against the use of a single shared infrastructure slice to serve the performance-sensitive traffic
from PLs. Also we evaluate the use of Time-Sensitive Networking (TSN) against bare Ethernet to
provide layer 2 connectivity among the 5G system components. We use a complete and realistic
setup based on experimental and simulation data of the scenario considered. Our results support the
effectiveness of infrastructure slicing to provide isolation in performance among the different slices.
Then, using dedicated slices with segregated resources for each PL might reduce the number of the
production downtimes and associated costs as the malfunctioning of a PL will not affect the network
performance perceived by the performance-sensitive traffic from other PLs. Last, our results show
that, besides the improvement in performance, TSN technology truly provides full isolation in the
transport network compared to standard Ethernet thanks to traffic prioritization, traffic regulation,
and bandwidth reservation capabilities.H2020 project 5G-CLARITY 871428Spanish Government PID2019-108713RB-C53TRUE-5
Automotive Ethernet architecture and security: challenges and technologies
Vehicle infrastructure must address the challenges posed by today's advances toward connected and autonomous vehicles. To allow for more flexible architectures, high-bandwidth connections and scalability are needed to connect many sensors and electronic control units (ECUs). At the same time, deterministic and low latency is a critical and significant design requirement to support urgent real-time applications in autonomous vehicles. As a recent solution, the time-sensitive network (TSN) was introduced as Ethernet-based amendments in IEEE 802.1 TSN standards to meet those needs. However, it had hurdle to be overcome before it can be used effectively. This paper discusses the latest studies concerning the automotive Ethernet requirements, including transmission delay studies to improve worst-case end-to-end delay and end-to-end jitter. Also, the paper focuses on the securing Ethernet-based in-vehicle networks (IVNs) by reviewing new encryption and authentication methods and approaches
Latency Analysis of Multiple Classes of AVB Traffic in TSN with Standard Credit Behavior using Network Calculus
Time-Sensitive Networking (TSN) is a set of amendments that extend Ethernet
to support distributed safety-critical and real-time applications in the
industrial automation, aerospace and automotive areas. TSN integrates multiple
traffic types and supports interactions in several combinations. In this paper
we consider the configuration supporting Scheduled Traffic (ST) traffic
scheduled based on Gate-Control-Lists (GCLs), Audio-Video-Bridging (AVB)
traffic according to IEEE 802.1BA that has bounded latencies, and Best-Effort
(BE) traffic, for which no guarantees are provided. The paper extends the
timing analysis method to multiple AVB classes and proofs the credit bounds for
multiple classes of AVB traffic, respectively under frozen and non-frozen
behaviors of credit during guard band (GB). They are prerequisites for
non-overflow credits of Credit-Based Shaper (CBS) and preventing starvation of
AVB traffic. Moreover, this paper proposes an improved timing analysis method
reducing the pessimism for the worst-case end-to-end delays of AVB traffic by
considering the limitations from the physical link rate and the output of CBS.
Finally, we evaluate the improved analysis method on both synthetic and
real-world test cases, showing the significant reduction of pessimism on
latency bounds compared to related work, and presenting the correctness
validation compared with simulation results. We also compare the AVB latency
bounds in the case of frozen and non-frozen credit during GB. Additionally, we
evaluate the scalability of our method with variation of the load of ST flows
and of the bandwidth reservation for AVB traffic
EDGAR: An Autonomous Driving Research Platform -- From Feature Development to Real-World Application
While current research and development of autonomous driving primarily
focuses on developing new features and algorithms, the transfer from isolated
software components into an entire software stack has been covered sparsely.
Besides that, due to the complexity of autonomous software stacks and public
road traffic, the optimal validation of entire stacks is an open research
problem. Our paper targets these two aspects. We present our autonomous
research vehicle EDGAR and its digital twin, a detailed virtual duplication of
the vehicle. While the vehicle's setup is closely related to the state of the
art, its virtual duplication is a valuable contribution as it is crucial for a
consistent validation process from simulation to real-world tests. In addition,
different development teams can work with the same model, making integration
and testing of the software stacks much easier, significantly accelerating the
development process. The real and virtual vehicles are embedded in a
comprehensive development environment, which is also introduced. All parameters
of the digital twin are provided open-source at
https://github.com/TUMFTM/edgar_digital_twin
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