55 research outputs found
A Survey of Scheduling in Time-Sensitive Networking (TSN)
TSN is an enhancement of Ethernet which provides various mechanisms for
real-time communication. Time-triggered (TT) traffic represents periodic data
streams with strict real-time requirements. Amongst others, TSN supports
scheduled transmission of TT streams, i.e., the transmission of their packets
by edge nodes is coordinated in such a way that none or very little queuing
delay occurs in intermediate nodes. TSN supports multiple priority queues per
egress port. The TAS uses so-called gates to explicitly allow and block these
queues for transmission on a short periodic timescale. The TAS is utilized to
protect scheduled traffic from other traffic to minimize its queuing delay. In
this work, we consider scheduling in TSN which comprises the computation of
periodic transmission instants at edge nodes and the periodic opening and
closing of queue gates.
In this paper, we first give a brief overview of TSN features and standards.
We state the TSN scheduling problem and explain common extensions which also
include optimization problems. We review scheduling and optimization methods
that have been used in this context. Then, the contribution of currently
available research work is surveyed. We extract and compile optimization
objectives, solved problem instances, and evaluation results. Research domains
are identified, and specific contributions are analyzed. Finally, we discuss
potential research directions and open problems.Comment: 34 pages, 19 figures, 9 tables 110 reference
Design Optimization of Cyber-Physical Distributed Systems using IEEE Time-sensitive Networks (TSN)
In this paper we are interested in safety-critical real-time applications implemented on distributed architectures supporting the Time-SensitiveNetworking (TSN) standard. The ongoing standardization of TSN is an IEEE effort to bring deterministic real-time capabilities into the IEEE 802.1 Ethernet standard supporting safety-critical systems and guaranteed Quality-of-Service. TSN will support Time-Triggered (TT) communication based on schedule tables, Audio-Video-Bridging (AVB) flows with bounded end-to-end latency as well as Best-Effort messages. We first present a survey of research related to the optimization of distributed cyber-physical systems using real-time Ethernet for communication. Then, we formulate two novel optimization problems related to the scheduling and routing of TT and AVB traffic in TSN. Thus, we consider that we know the topology of the network as well as the set of TT and AVB flows. We are interested to determine the routing of both TT and AVB flows as well as the scheduling of the TT flows such that all frames are schedulable and the AVB worst-case end-to-end delay is minimized. We have proposed an Integer Linear Programming (ILP) formulation for the scheduling problem and a Greedy Randomized Adaptive Search Procedure (GRASP)-based heuristic for the routing problem. The proposed approaches have been evaluated using several test cases
Simulation of Mixed Critical In-vehicular Networks
Future automotive applications ranging from advanced driver assistance to
autonomous driving will largely increase demands on in-vehicular networks. Data
flows of high bandwidth or low latency requirements, but in particular many
additional communication relations will introduce a new level of complexity to
the in-car communication system. It is expected that future communication
backbones which interconnect sensors and actuators with ECU in cars will be
built on Ethernet technologies. However, signalling from different application
domains demands for network services of tailored attributes, including
real-time transmission protocols as defined in the TSN Ethernet extensions.
These QoS constraints will increase network complexity even further.
Event-based simulation is a key technology to master the challenges of an
in-car network design. This chapter introduces the domain-specific aspects and
simulation models for in-vehicular networks and presents an overview of the
car-centric network design process. Starting from a domain specific description
language, we cover the corresponding simulation models with their workflows and
apply our approach to a related case study for an in-car network of a premium
car
TSN-Based Automotive E/E Architecture
Time-Sensitive Networking, also known as TSN, is a deterministic network based on traditional Ethernet. It offers a bunch of standards or profiles specified by IEEE 802.1 task group which has been evolved from the former IEEE802.1 Audio Video Bridging task group. In Automotive Industry, especially in ADAS domain, TSN backbone communication will gradually merge with or even replace the traditional in-vechile communication like CAN/CANFD/LIN/MOST/FlexRay due to below properties, it plays a key bridge role in heterogeneous SOC communication network
Quantitative Performance Comparison of Various Traffic Shapers in Time-Sensitive Networking
Owning to the sub-standards being developed by IEEE Time-Sensitive Networking
(TSN) Task Group, the traditional IEEE 802.1 Ethernet is enhanced to support
real-time dependable communications for future time- and safety-critical
applications. Several sub-standards have been recently proposed that introduce
various traffic shapers (e.g., Time-Aware Shaper (TAS), Asynchronous Traffic
Shaper (ATS), Credit-Based Shaper (CBS), Strict Priority (SP)) for flow control
mechanisms of queuing and scheduling, targeting different application
requirements. These shapers can be used in isolation or in combination and
there is limited work that analyzes, evaluates and compares their performance,
which makes it challenging for end-users to choose the right combination for
their applications. This paper aims at (i) quantitatively comparing various
traffic shapers and their combinations, (ii) summarizing, classifying and
extending the architectures of individual and combined traffic shapers and
their Network calculus (NC)-based performance analysis methods and (iii)
filling the gap in the timing analysis research on handling two novel hybrid
architectures of combined traffic shapers, i.e., TAS+ATS+SP and TAS+ATS+CBS. A
large number of experiments, using both synthetic and realistic test cases, are
carried out for quantitative performance comparisons of various individual and
combined traffic shapers, from the perspective of upper bounds of delay,
backlog and jitter. To the best of our knowledge, we are the first to
quantitatively compare the performance of the main traffic shapers in TSN. The
paper aims at supporting the researchers and practitioners in the selection of
suitable TSN sub-protocols for their use cases
Real-Time Scheduling for Time-Sensitive Networking: A Systematic Review and Experimental Study
Time-Sensitive Networking (TSN) has been recognized as one of the key
enabling technologies for Industry 4.0 and has been deployed in many time- and
mission-critical industrial applications, e.g., automotive and aerospace
systems. Given the stringent real-time communication requirements raised by
these applications, the Time-Aware Shaper (TAS) draws special attention among
the many traffic shapers developed for TSN, due to its ability to achieve
deterministic latency guarantees. Extensive efforts on the designs of
scheduling methods for TAS shapers have been reported in recent years to
improve the system schedulability, each with their own distinct focuses and
concerns. However, these scheduling methods have yet to be thoroughly
evaluated, especially through experimental comparisons, to provide a
systematical understanding on their performance using different evaluation
metrics in various application scenarios. In this paper, we fill this gap by
presenting a comprehensive experimental study on the existing TAS-based
scheduling methods for TSN. We first categorize the system models employed in
these work along with their formulated problems, and outline the fundamental
considerations in the designs of TAS-based scheduling methods. We then perform
extensive evaluation on 16 representative solutions and compare their
performance under both synthetic scenarios and real-life industrial use cases.
Through these experimental studies, we identify the limitations of individual
scheduling methods and highlight several important findings. This work will
provide foundational knowledge for the future studies on TSN real-time
scheduling problems, and serve as the performance benchmarking for scheduling
method development in TSN.Comment: 22 pages, ac
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