Control-guided Communication: Efficient Resource Arbitration and Allocation in Multi-hop Wireless Control Systems

In future autonomous systems, wireless multi-hop communication is key to enable collaboration among distributed agents at low cost and high flexibility. When many agents need to transmit information over the same wireless network, communication becomes a shared and contested resource. Event-triggered and self-triggered control account for this by transmitting data only when needed, enabling significant energy savings. However, a solution that brings those benefits to multi-hop networks and can reallocate freed up bandwidth to additional agents or data sources is still missing. To fill this gap, we propose control-guided communication, a novel co-design approach for distributed self-triggered control over wireless multi-hop networks. The control system informs the communication system of its transmission demands ahead of time, and the communication system allocates resources accordingly. Experiments on a cyber-physical testbed show that multiple cart-poles can be synchronized over wireless, while serving other traffic when resources are available, or saving energy. These experiments are the first to demonstrate and evaluate distributed self-triggered control over low-power multi-hop wireless networks at update rates of tens of milliseconds.Comment: Accepted final version to appear in: IEEE Control Systems Letter

A qualitative cybersecurity analysis of time-triggered communication networks in automotive systems

© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/).Security is gaining increasing importance in automotive systems, driven by technical innovations. For example, automotive vehicles become more open systems, allowing the communication with other traffic participants and road infrastructure. Also, automotive vehicles are provided with increased autonomy which raises severe safety concerns, and consequently also security concerns – both concerns that interweave in such systems. In this paper we present a qualitative cybersecurity analysis by comparing different time-triggered (TT) communication networks. While TT communication networks have been analysed extensively for dependability, the contribution of this work is to identify security-related benefits that TT communication networks can provide. In particular, their mechanisms for spacial and temporal encapsulation of network traffic are instrumental to improve network security. The security arguments can be used as a design guide for implementing critical communication in flexible network standards like TSN.Peer reviewe

Overcoming Bandwidth Limitations in Wireless Sensor Networks by Exploitation of Cyclic Signal Patterns: An Event-triggered Learning Approach

Wireless sensor networks are used in a wide range of applications, many of which require real-time transmission of the measurements. Bandwidth limitations result in limitations on the sampling frequency and number of sensors. This problem can be addressed by reducing the communication load via data compression and event-based communication approaches. The present paper focuses on the class of applications in which the signals exhibit unknown and potentially time-varying cyclic patterns. We review recently proposed event-triggered learning (ETL) methods that identify and exploit these cyclic patterns, we show how these methods can be applied to the nonlinear multivariable dynamics of three-dimensional orientation data, and we propose a novel approach that uses Gaussian process models. In contrast to other approaches, all three ETL methods work in real time and assure a small upper bound on the reconstruction error. The proposed methods are compared to several conventional approaches in experimental data from human subjects walking with a wearable inertial sensor network. They are found to reduce the communication load by 60–70%, which implies that two to three times more sensor nodes could be used at the same bandwidth

Flexible time-triggered protocol for CAN: new scheduling and dispatching solutions

One of the possibilities to build robust communication systems with respect to their temporal behaviour is to use autonomous control based on the time-triggered paradigm. The FTT-CAN - flexible time-triggered protocol, relies on centralised scheduling but makes use of the CAN native distributed arbitration to reduce communication overhead. There, a planning scheduler is used within a master node to reduce the scheduling run-time overhead. On-line changes to the communication requirements can then be made under guaranteed timeliness. In addition FTT-CAN also allows an efficient combination of both time-triggered and event- triggered traffic with temporal isolation. In this paper, recent evolutions of the initial protocol definition concerning transmission of synchronous and asynchronous messages are presented. These consist in a time division of the elementary transmission window which optimises the available bandwidth for asynchronous messages, keeping the timeliness of synchronous messages without jeopardising their transmission jitter. A novel solution for the planning scheduler is also presented. It consists in an FPGA-based coprocessor which implements the planning scheduler technique without imposing overhead to the arbiter CPU. With it, it is possible to reduce strongly the plan duration thus allowing on-line admission demanded by system elements and, also, to extend the protocol application to high-speed networks

A journey into time-triggered communication protocols with a focus on Ethernet TSN

This presentation provides an historical perspective on time-triggered (TT) protocols and highlights a few possible misconceptions about TT communication. The presentation is organized as follows: 1) landscape of real-time (wired) communication networks, 2) Time-triggered (TT) protocols evolution: TTP, FlexRay, TTEthernet, TSN/TAS (IEEE802.1Qbv) 3) Misconceptions about TT communication 4) Takeaways and what is ahead of us

Just a Second -- Scheduling Thousands of Time-Triggered Streams in Large-Scale Networks

Deterministic real-time communication with bounded delay is an essential requirement for many safety-critical cyber-physical systems, and has received much attention from major standardization bodies such as IEEE and IETF. In particular, Ethernet technology has been extended by time-triggered scheduling mechanisms in standards like TTEthernet and Time-Sensitive Networking. Although the scheduling mechanisms have become part of standards, the traffic planning algorithms to create time-triggered schedules are still an open and challenging research question due to the problem's high complexity. In particular, so-called plug-and-produce scenarios require the ability to extend schedules on the fly within seconds. The need for scalable scheduling and routing algorithms is further supported by large-scale distributed real-time systems like smart energy grids with tight communication requirements. In this paper, we tackle this challenge by proposing two novel algorithms called Hierarchical Heuristic Scheduling (H2S) and Cost-Efficient Lazy Forwarding Scheduling (CELF) to calculate time-triggered schedules for TTEthernet. H2S and CELF are highly efficient and scalable, calculating schedules for more than 45,000 streams on random networks with 1,000 bridges as well as a realistic energy grid network within sub-seconds to seconds

Synchronization of decentralized event-triggered uncertain switched neural networks with two additive time-varying delays

This paper addresses the problem of synchronization for decentralized event-triggered uncertain switched neural networks with two additive time-varying delays. A decentralized eventtriggered scheme is employed to determine the time instants of communication from the sensors to the central controller based on narrow possible information only. In addition, a class of switched neural networks is analyzed based on the Lyapunov–Krasovskii functional method and a combined linear matrix inequality (LMI) technique and average dwell time approach. Some sufficient conditions are derived to guarantee the exponential stability of neural networks under consideration in the presence of admissible parametric uncertainties. Numerical examples are provided to illustrate the effectiveness of the obtained results.&nbsp