A Hardware Time Manager Implementation for the Xenomai Real-Time Kernel of Embedded Linux

Nowadays, the use of embedded operating systems in different embedded projects is subject to a tremendous growth. Embedded Linux is becoming one of those most popular EOSs due to its modularity, efficiency, reliability, and cost. One way to make it hard real-time is to include a real-time kernel like Xenomai. One of the key characteristics of a Real-Time Operating System (RTOS) is its ability to meet execution time deadlines deterministically. So, the more precise and flexible the time management can be, the better it can handle efficiently the determinism for different embedded applications. RTOS time precision is characterized by a specific periodic interrupt service controlled by a software time manager. The smaller the period of the interrupt, the better the precision of the RTOS, the more it overloads the CPU, and though reduces the overall efficiency of the RTOS. In this paper, we propose to drastically reduce these overheads by migrating the time management service of Xenomai into a configurable hardware component to relieve the CPU. The hardware component is implemented in a Field Programmable Gate Array coupled to the CPU. This work was achieved in a Master degree project where students could apprehend many fields of embedded systems: RTOS programming, hardware design, performance evaluation, etc.Comment: Embed With Linux (EWiLi) workshop, Lorient : France (2012

Joint Time-and Event-Triggered Scheduling in the Linux Kernel

There is increasing interest in using Linux in the real-time domain due to the emergence of cloud and edge computing, the need to decrease costs, and the growing number of complex functional and non-functional requirements of real-time applications. Linux presents a valuable opportunity as it has rich hardware support, an open-source development model, a well-established programming environment, and avoids vendor lock-in. Although Linux was initially developed as a general-purpose operating system, some real-time capabilities have been added to the kernel over many years to increase its predictability and reduce its scheduling latency. Unfortunately, Linux currently has no support for time-triggered (TT) scheduling, which is widely used in the safety-critical domain for its determinism, low run-time scheduling latency, and strong isolation properties. We present an enhancement of the Linux scheduler as a new low-overhead TT scheduling class to support offline table-driven scheduling of tasks on multicore Linux nodes. Inspired by the Slot shifting algorithm, we complement the new scheduling class with a low overhead slot shifting manager running on a non-time-triggered core to provide guaranteed execution time to real-time aperiodic tasks by using the slack of the time-triggered tasks and avoiding high-overhead table regeneration for adding new periodic tasks. Furthermore, we evaluate our implementation on server-grade hardware with Intel Xeon Scalable Processor.Comment: to appear in Operating Systems Platforms for Embedded Real-Time applications (OSPERT) workshop 2023 co-hosted with 35th Euromicro conference on Real-time system

RThybrid: A standardized and open-source real-time software model library for experimental neuroscience

Closed-loop technologies provide novel ways of online observation, control and bidirectional interaction with the nervous system, which help to study complex non-linear and partially observable neural dynamics. These protocols are often difficult to implement due to the temporal precision required when interacting with biological components, which in many cases can only be achieved using real-time technology. In this paper we introduce RTHybrid (www.github.com/GNB-UAM/RTHybrid), a free and open-source software that includes a neuron and synapse model library to build hybrid circuits with living neurons in a wide variety of experimental contexts. In an effort to encourage the standardization of real-time software technology in neuroscience research, we compared different open-source real-time operating system patches, RTAI, Xenomai 3 and Preempt-RT, according to their performance and usability. RTHybrid has been developed to run over Linux operating systems supporting both Xenomai 3 and Preempt-RT real-time patches, and thus allowing an easy implementation in any laboratory. We report a set of validation tests and latency benchmarks for the construction of hybrid circuits using this library. With this work we want to promote the dissemination of standardized, user-friendly and open-source software tools developed for open- and closed-loop experimental neuroscience.This work was supported by MINECO/FEDER DPI2015-65833-P, TIN2017-84452-R and ONRG grant N62909-14-1-N27

An Android real-time kernel and system interface for open nano-satellite constellations

L'objectiu d'aquest treball és dissenyar i implementar part de l'arquitectura de software per a una plataforma de desenvolupament de nano-satèl·lits oberta basada en Android. Per un costat, afegir temps real al kernel. Per un altre costat, implementar un repartidor de missatges modular i flexible.The aim of this thesis is to design and implement part of the software architecture for an open nano-satellite development platform based on an Android smartphone. On one side, extend the kernel with real-time capabilities. On the other side, implement a flexible and modular message distributor

A Scalable, High-Performance, Real-Time Control Architecture with Application to Semi-Autonomous Teleoperation

A scalable and real-time capable infrastructure is required to enable high-performance control and haptic rendering of systems with many degrees-of-freedom. The specific platform that motivates this thesis work is the open research platform da Vinci ReResearch Kit (dVRK). For the system architecture, we propose a specialized IEEE-1394 (FireWire) broadcast protocol that takes advantage of broadcast and peer-to-peer transfers to minimize the number of transactions, and thus the software overhead, on the control PC, thereby enabling fast real-time control. It has also been extended to Ethernet via a novel Ethernet-to-FireWire bridge protocol. The software architecture consists of a distributed hardware interface layer, a real-time component-based software framework, and integration with the Robot Operating System (ROS). The architecture is scalable to support multiple active manipulators, reconfigurable to enable researchers to partition a full system into multiple independent subsystems, and extensible at all levels of control. This architecture has been applied to two semi-autonomous teleoperation applications. The first application is a suturing task in Robotic Minimally Invasive Surgery (RMIS), that includes the development of virtual fixtures for the needle passing and knot tying sub-tasks, with a multi-user study to verify their effectiveness. The second application concerns time-delayed teleoperation of a robotic arm for satellite servicing. The research contribution includes the development of a line virtual fixture with augmented reality, a test for different time delay configurations and a multi-user study that evaluates the effectiveness of the system

Adaptive Resource Management for Uncertain Execution Platforms

Embedded systems are becoming increasingly complex. At the same time, the components that make up the system grow more uncertain in their properties. For example, current developments in CPU design focuses on optimizing for average performance rather than better worst case performance. This, combined with presence of 3rd party software components with unknown properties, makes resource management using prior knowledge less and less feasible. This thesis presents results on how to model software components so that resource allocation decisions can be made on-line. Both the single and multiple resource case is considered as well as extending the models to include resource constraints based on hardware dynam- ics. Techniques for estimating component parameters on-line are presented. Also presented is an algorithm for computing an optimal allocation based on a set of convex utility functions. The algorithm is designed to be computationally efficient and to use simple mathematical expres- sions that are suitable for fixed point arithmetics. An implementation of the algorithm and results from experiments is presented, showing that an adaptive strategy using both estimation and optimization can outperform a static approach in cases where uncertainty is high