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Time-Sensitive Networking (TSN) is designed for real-time applications, usually pertaining to a set of Time-Triggered (TT) data flows. TT traffic generally requires low packet loss and guaranteed upper bounds on end-to-end delay. To guarantee the end-to-end delay bounds, TSN uses Time-Aware Shaper (TAS) to provide deterministic service to TT flows. Each frame of TT traffic is scheduled a specific time slot at each switch for its transmission. Several factors may influence frame transmissions, which then impact the scheduling in the whole network. These factors may cause frames sent in wrong time slots, namely misbehaviors. To mitigate the occurrence of misbehaviors, we need to find proper scheduling for the whole network. In our research, we use a reinforcement-learning model, which is called Deep Deterministic Policy Gradient (DDPG), to find the suitable scheduling. DDPG is used to model the uncertainty caused by the transmission-influencing factors such as time-synchronization errors. Compared with the state of the art, our approach using DDPG significantly decreases the number of misbehaviors in TSN scenarios studied and improves the delay performance of the network. 

AFDX (Avionics Full Duplex Switched Ethernet) is developed to support mission-critical communications while providing deterministic Quality of Service (QoS) across cyber-physical avionics systems. Currently, AFDX utilizes FP/FIFO QoS mechanisms to guarantee its real-time performance. To analyze the real-time performance of avionic systems in their design processes, existing work analyzes the deterministic delay bound of AFDX using NC (Network Calculus). However, existing analytical work is based on an unrealistic assumption leading to assumed worst cases that may not be achievable in reality. In this paper, we present a family of algorithms that can search for realistic worst-case delay scenarios in both preemptive and non-preemptive situations. Then we integrate the proposed algorithms with NC and apply our approach to analyzing tandem AFDX networks. Our reality-conforming approach yields tighter delay bound estimations than the state of the art. When there are 100 virtual links in AFDX networks, our method can provide delay bounds more than 25% tighter than those calculated by the state of the art in our evaluation. Moreover, when using our reality-conforming method in the design process, it leads to 27.2% increase in the number of virtual links accommodated by the network in the tandem scenario. 

This paper studies the current status and future directions of RTOS (Real-Time Operating Systems) for time-sensitive CPS (Cyber-Physical Systems). GPOS (General Purpose Operating Systems) existed before RTOS but did not meet performance requirements for time sensitive CPS. Many GPOS have put forward adaptations to meet the requirements of real-time performance, and this paper compares RTOS and GPOS and shows their pros and cons for CPS applications. Furthermore, comparisons among select RTOS such as VxWorks, RTLinux, and FreeRTOS have been conducted in terms of scheduling, kernel, and priority inversion. Various tools for WCET (Worst-Case Execution Time) estimation are discussed. This paper also presents a CPS use case of RTOS, i.e. JetOS for avionics, and future advancements in RTOS such as multi-core RTOS, new RTOS architecture and RTOS security for CPS. 

Recently, switched Ethernet has become increasingly popular in networked cyber-physical systems (NCPS). In an Ethernet-based NCPS, network-connected devices (e.g., sensors and actuators) realize time-critical tasks by exchanging miscellaneous information, such as sensor readings and control commands. To ensure reliable control and operation, network-induced delays for time-critical NCPS applications must be carefully examined. In this work, we propose a framework combining network delay measurements and network-calculus-based delay performance analysis to obtain accurate, deterministic worst-case delay bounds for NCPS. By modeling traffic sources and networking devices (e.g., Ethernet switches) through measurements, we establish accurate traffic and device models for network-calculus-based analysis. To obtain worst-case delay bounds, different network-calculus-based analytical methods can be leveraged, allowing CPS architects to customize the proposed delay analysis framework to suit application-specific needs. Our evaluation results show that the proposed approach derives accurate delay bounds, making it a valuable tool for architects designing NCPSs supporting time-critical applications. 

Recently, wireless communication technologies, such as Wireless Local Area Networks (WLANs), have gained increasing popularity in industrial control systems (ICSs) due to their low cost and ease of deployment, but communication delays associated with these technologies make it unsuitable for critical real-time and safety applications. To address concerns on network-induced delays of wireless communication technologies and bring their advantages into modern ICSs, wireless network infrastructure based on the Parallel Redundancy Protocol (PRP) has been proposed. Although application-specific simulations and measurements have been conducted to show that wireless network infrastructure based on PRP can be a viable solution for critical applications with stringent delay performance constraints, little has been done to devise an analytical framework facilitating the adoption of wireless PRP infrastructure in miscellaneous ICSs. Leveraging the deterministic network calculus (DNC) theory, we propose to analytically derive worst-case bounds on network- induced delays for critical ICS applications. We show that the problem of worst-case delay bounding for a wireless PRP network can be solved by performing network-calculus-based analysis on its non-feedforward traffic pattern. Closed-form expressions of worst-case delays are derived, which has not been found previously and allows ICS architects/designers to compute worst- case delay bounds for ICS tasks in their respective application domains of interest. Our analytical results not only provide insights into the impacts of network-induced delays on latency- critical tasks but also allow ICS architects/operators to assess whether proper wireless RPR network infrastructure can be adopted into their systems. 

In this work, we propose to derive realistic, accurate bounds on network-induced delays for time-critical tasks running on Avionics Full-Duplex Switched Ethernet. In the WiP poster, we present preliminary evaluation results showing that through measurement-based modeling and refining network-calculus-based analysis with measurements, tight delay bounds can be obtained for AFDX networks with realistic traffic patterns and network workloads.