Semantics-Preserving Implementation of Synchronous Specifications Over Dynamic TDMA Distributed Architectures

International audienceWe propose a technique to automatically synthesize programs and schedules for hard real-time distributed (embedded) systems from synchronous data-flow models. Our technique connects the SynDEx scheduling tool and the Network Code toolchain in a seamless flow of automatic model transformations that go all the way from specification to implementation. Our contribution is the non-trivial connection between the models manipulated by SynDEx and by the Network Code toolchain, at both formal and tool level. We provide an algorithm for converting the data-dependent schedule tables output by SynDEx into Network Code programs which can be seen as an ``assembly code'' level for time-driven distributed real-time systems. The main difficulty is to ensure the preservation of both functionality and the real-time guarantees computed by SynDEx in the presence of clock drifts (which are abstracted away in the scheduling model of SynDEx). Existing tools can convert the resulting Network Code programs into software and hardware-accelerated execution units.Nous proposons une technique pour la synthèse automatique de programmes et ordonnancements pour des systèmes temps-réel (embarqués) distribués, à partir de spécifications synchrones flot de données

Learning and testing stochastic discrete event

Dissertação de mestrado em Engenharia de InformáticaSistemas de eventos discretos (DES) são uma importante subclasse de sistemas (à luz da teoria dos sistemas). Estes têm sido usados, particularmente na indústria para analisar e modelar um vasto conjunto de sistemas reais, tais como, sistemas de produção, sistemas de computador, sistemas de controlo de tráfego e sistemas híbridos. O nosso trabalho explora uma extensão de DES com ênfase nos processos estocásticos, comummente chamado como sistemas de eventos discretos estocásticos (SDES). Existe assim a necessidade de estabelecer uma abstração estocástica através do uso de processos semi-Markovianos generalizados (GSMP) para SDES. Assim, o objetivo do nosso trabalho é propor uma metodologia e um conjunto de algoritmos para aprendizagem de GSMP, usar técnicas de model-checking estatístico para a verificação e propor duas novas abordagens para teste de DES e SDES (respetivamente, não estocasticamente e estocasticamente). Este trabalho também introduz uma noção de modelação, analise e verificação de sistemas contínuos e modelos de perturbação no contexto da verificação por model-checking estatístico.Discrete event systems (DES) are an important subclass of systems (in systems theory). They have been used, particularly in industry, to analyze and model a wide variety of real systems, such as production systems, computer systems, traffic systems, and hybrid systems. Our work explores an extension of DES with an emphasis on stochastic processes, commonly called stochastic discrete event systems (SDES). There was a need to establish a stochastic abstraction for SDES through generalized semi-Markov processes (GSMP). Thus, the aim of our work is to propose a methodology and a set of algorithms for GSMP learning, using model checking techniques for verification, and to propose two new approaches for testing DES and SDES (non-stochastically and stochastically). This work also introduces a notion of modeling, analysis, and verification of continuous systems and disturbance models in the context of verifiable statistical model checking

Development of Advanced Closed-Loop Brain Electrophysiology Systems for Freely Behaving Rodents

[ES] La electrofisiología extracelular es una técnica ampliamente usada en investigación neurocientífica, la cual estudia el funcionamiento del cerebro mediante la medición de campos eléctricos generados por la actividad neuronal. Esto se realiza a través de electrodos implantados en el cerebro y conectados a dispositivos electrónicos para amplificación y digitalización de las señales. De los muchos modelos animales usados en experimentación, las ratas y los ratones se encuentran entre las especies más comúnmente utilizadas. Actualmente, la experimentación electrofisiológica busca condiciones cada vez más complejas, limitadas por la tecnología de los dispositivos de adquisición. Dos aspectos son de particular interés: Realimentación de lazo cerrado y comportamiento en condiciones naturales. En esta tesis se presentan desarrollos con el objetivo de mejorar diferentes facetas de estos dos problemas. La realimentación en lazo cerrado se refiere a todas las técnicas en las que los estímulos son producidos en respuesta a un evento generado por el animal. La latencia debe ajustarse a las escalas temporales bajo estudio. Los sistemas modernos de adquisición presentan latencias en el orden de los 10ms. Sin embargo, para responder a eventos rápidos, como pueden ser los potenciales de acción, se requieren latencias por debajo de 1ms. Además, los algoritmos para detectar los eventos o generar los estímulos pueden ser complejos, integrando varias entradas de datos en tiempo real. Integrar el desarrollo de dichos algoritmos en las herramientas de adquisición forma parte del diseño experimental. Para estudiar comportamientos naturales, los animales deben ser capaces de moverse libremente en entornos emulando condiciones naturales. Experimentos de este tipo se ven dificultados por la naturaleza cableada de los sistemas de adquisición. Otras restricciones físicas, como el peso de los implantes o limitaciones en el consumo de energía, pueden también afectar a la duración de los experimentos, limitándola. La experimentación puede verse enriquecida cuando los datos electrofisiológicos se ven complementados con múltiples fuentes distintas. Por ejemplo, seguimiento de los animales o miscroscopía. Herramientas capaces de integrar datos independientemente de su origen abren la puerta a nuevas posibilidades. Los avances tecnológicos presentados abordan estas limitaciones. Se han diseñado dispositivos con latencias de lazo cerrado inferiores a 200us que permiten combinar cientos de canales electrofisiológicos con otras fuentes de datos, como vídeo o seguimiento. El software de control para estos dispositivos se ha diseñado manteniendo la flexibilidad como objetivo. Se han desarrollado interfaces y estándares de naturaleza abierta para incentivar el desarrollo de herramientas compatibles entre ellas. Para resolver los problemas de cableado se siguieron dos métodos distintos. Uno fue el desarrollo de headstages ligeros combinados con cables coaxiales ultra finos y conmutadores activos, gracias al seguimiento de animales. Este desarrollo permite reducir el esfuerzo impuesto a los animales, permitiendo espacios amplios y experimentos de larga duración, al tiempo que permite el uso de headstages con características avanzadas. Paralelamente se desarrolló un tipo diferente de headstage, con tecnología inalámbrica. Se creó un algoritmo de compresión digital especializado capaz de reducir el ancho de banda a menos del 65% de su tamaño original, ahorrando energía. Esta reducción permite baterías más ligeras y mayores tiempos de operación. El algoritmo fue diseñado para ser capaz de ser implementado en una gran variedad de dispositivos. Los desarrollos presentados abren la puerta a nuevas posibilidades experimentales para la neurociencia, combinando adquisición elextrofisiológica con estudios conductuales en condiciones naturales y estímulos complejos en tiempo real.[CA] L'electrofisiologia extracel·lular és una tècnica àmpliament utilitzada en la investigació neurocientífica, la qual permet estudiar el funcionament del cervell mitjançant el mesurament de camps elèctrics generats per l'activitat neuronal. Això es realitza a través d'elèctrodes implantats al cervell, connectats a dispositius electrònics per a l'amplificació i digitalització dels senyals. Dels molts models animals utilitzats en experimentació electrofisiològica, les rates i els ratolins es troben entre les espècies més utilitzades. Actualment, l'experimentació electrofisiològica busca condicions cada vegada més complexes, limitades per la tecnologia dels dispositius d'adquisició. Dos aspectes són d'especial interès: La realimentació de sistemes de llaç tancat i el comportament en condicions naturals. En aquesta tesi es presenten desenvolupaments amb l'objectiu de millorar diferents aspectes d'aquestos dos problemes. La realimentació de sistemes de llaç tancat es refereix a totes aquestes tècniques on els estímuls es produeixen en resposta a un esdeveniment generat per l'animal. La latència ha d'ajustar-se a les escales temporals sota estudi. Els sistemes moderns d'adquisició presenten latències en l'ordre dels 10ms. No obstant això, per a respondre a esdeveniments ràpids, com poden ser els potencials d'acció, es requereixen latències per davall de 1ms. A més a més, els algoritmes per a detectar els esdeveniments o generar els estímuls poden ser complexos, integrant varies entrades de dades a temps real. Integrar el desenvolupament d'aquests algoritmes en les eines d'adquisició forma part del disseny dels experiments. Per a estudiar comportaments naturals, els animals han de ser capaços de moure's lliurement en ambients emulant condicions naturals. Aquestos experiments es veuen limitats per la natura cablejada dels sistemes d'adquisició. Altres restriccions físiques, com el pes dels implants o el consum d'energia, poden també limitar la duració dels experiments. L'experimentació es pot enriquir quan les dades electrofisiològiques es complementen amb dades de múltiples fonts. Per exemple, el seguiment d'animals o microscòpia. Eines capaces d'integrar dades independentment del seu origen obrin la porta a noves possibilitats. Els avanços tecnològics presentats tracten aquestes limitacions. S'han dissenyat dispositius amb latències de llaç tancat inferiors a 200us que permeten combinar centenars de canals electrofisiològics amb altres fonts de dades, com vídeo o seguiment. El software de control per a aquests dispositius s'ha dissenyat mantenint la flexibilitat com a objectiu. S'han desenvolupat interfícies i estàndards de naturalesa oberta per a incentivar el desenvolupament d'eines compatibles entre elles. Per a resoldre els problemes de cablejat es van seguir dos mètodes diferents. Un va ser el desenvolupament de headstages lleugers combinats amb cables coaxials ultra fins i commutadors actius, gràcies al seguiment d'animals. Aquest desenvolupament permet reduir al mínim l'esforç imposat als animals, permetent espais amplis i experiments de llarga durada, al mateix temps que permet l'ús de headstages amb característiques avançades. Paral·lelament es va desenvolupar un tipus diferent de headstage, amb tecnologia sense fil. Es va crear un algorisme de compressió digital especialitzat capaç de reduir l'amplada de banda a menys del 65% de la seua grandària original, estalviant energia. Aquesta reducció permet bateries més lleugeres i majors temps d'operació. L'algorisme va ser dissenyat per a ser capaç de ser implementat a una gran varietat de dispositius. Els desenvolupaments presentats obrin la porta a noves possibilitats experimentals per a la neurociència, combinant l'adquisició electrofisiològica amb estudis conductuals en condicions naturals i estímuls complexos en temps real.[EN] Extracellular electrophysiology is a technique widely used in neuroscience research. It can offer insights on how the brain works by measuring the electrical fields generated by neural activity. This is done through electrodes implanted in the brain and connected to amplification and digitization electronic circuitry. Of the many animal models used in electrophysiology experimentation, rodents such as rats and mice are among the most popular species. Modern electrophysiology experiments seek increasingly complex conditions that are limited by acquisition hardware technology. Two particular aspects are of special interest: Closed-loop feedback and naturalistic behavior. In this thesis, we present developments aiming to improve on different facets of these two problems. Closed-loop feedback encompasses all techniques in which stimuli is produced in response of an event generated by the animal. Latency, the time between trigger event and stimuli generation, must adjust to the biological timescale being studied. While modern acquisition systems feature latencies in the order of 10ms, response to fast events such as high-frequency electrical transients created by neuronal activity require latencies under $1ms$. In addition, algorithms for triggering or generating closed-loop stimuli can be complex, integrating multiple inputs in real-time. Integration of algorithm development into acquisition tools becomes an important part of experiment design. For electrophysiology experiments featuring naturalistic behavior, animals must be able to move freely in ecologically meaningful environments, mimicking natural conditions. Experiments featuring elements such as large arenaa, environmental objects or the presence of another animals are, however, hindered by the wired nature of acquisition systems. Other physical constraints, such as implant weight or power restrictions can also affect experiment time, limiting their duration. Beyond the technical limits, complex experiments are enriched when electrophysiology data is integrated with multiple sources, for example animal tracking or brain microscopy. Tools allowing mixing data independently of the source open new experimental possibilities. The technological advances presented on this thesis addresses these topics. We have designed devices with closed-loop latencies under 200us while featuring high-bandwidth interfaces. These allow the simultaneous acquisition of hundreds of electrophysiological channels combined with other heterogeneous data sources, such as video or tracking. The control software for these devices was designed with flexibility in mind, allowing easy implementation of closed-loop algorithms. Open interface standards were created to encourage the development of interoperable tools for experimental data integration. To solve wiring issues in behavioral experiments, we followed two different approaches. One was the design of light headstages, coupled with ultra-thin coaxial cables and active commutator technology, making use of animal tracking. This allowed to reduce animal strain to a minimum allowing large arenas and prolonged experiments with advanced headstages. A different, wireless headstage was also developed. We created a digital compression algorithm specialized for neural electrophysiological signals able to reduce data bandwidth to less than 65.5% its original size without introducing distortions. Bandwidth has a large effect on power requirements. Thus, this reduction allows for lighter batteries and extended operational time. The algorithm is designed to be able to be implemented in a wide variety of devices, requiring low hardware resources and adding negligible power requirements to a system. Combined, the developments we present open new possibilities for neuroscience experiments combining electrophysiology acquisition with natural behaviors and complex, real-time, stimuli.The research described in this thesis was carried out at the Polytechnic University of Valencia (Universitat Politècnica de València), Valencia, Spain in an extremely close collaboration with the Neuroscience Institute - Spanish National Research Council - Miguel Hernández University (Instituto de Neurociencias - Consejo Superior de Investigaciones Cientí cas - Universidad Miguel Hernández), San Juan de Alicante, Spain. The projects described in chapters 3 and 4 were developed in collabo- ration with, and funded by, Open Ephys, Cambridge, MA, USA and OEPS - Eléctronica e produção, unipessoal lda, Algés, Portugal.Cuevas López, A. (2021). Development of Advanced Closed-Loop Brain Electrophysiology Systems for Freely Behaving Rodents [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/179718TESI

Translational pipelines for closed-loop neuromodulation

Closed-loop neuromodulation systems have shown significant potential for addressing unmet needs in the treatment of disorders of the central nervous system, yet progress towards clinical adoption has been slow. Advanced technological developments often stall in the preclinical stage by failing to account for the constraints of implantable medical devices, and due to the lack of research platforms with a translational focus. This thesis presents the development of three clinically relevant research systems focusing on refinements of deep brain stimulation therapies. First, we introduce a system for synchronising implanted and external stimulation devices, allowing for research into multi-site stimulation paradigms, cross-region neural plasticity, and questions of phase coupling. The proposed design aims to sidestep the limited communication capabilities of existing commercial implant systems in providing a stimulation state readout without reliance on telemetry, creating a cross-platform research tool. Next, we present work on the Picostim-DyNeuMo adaptive neuromodulation platform, focusing on expanding device capabilities from activity and circadian adaptation to bioelectric marker--based responsive stimulation. Here, we introduce a computationally optimised implementation of a popular band power--estimation algorithm suitable for deployment in the DyNeuMo system. The new algorithmic capability was externally validated to establish neural state classification performance in two widely-researched use cases: Parkinsonian beta bursts and seizures. For in vivo validation, a pilot experiment is presented demonstrating responsive neurostimulation to cortical alpha-band activity in a non-human primate model for the modulation of attention state. Finally, we turn our focus to the validation of a recently developed method to provide computationally efficient real-time phase estimation. Following theoretical analysis, the method is integrated into the commonly used Intan electrophysiological recording platform, creating a novel closed-loop optogenetics research platform. The performance of the research system is characterised through a pilot experiment, targeting the modulation of cortical theta-band activity in a transgenic mouse model

MediaSync: Handbook on Multimedia Synchronization

This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences

Software engineering: Testing real-time embedded systems using timed automata based approaches

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Real-time Embedded Systems (RTESs) have an increasing role in controlling society infrastructures that we use on a day-to-day basis. RTES behaviour is not based solely on the interactions it might have with its surrounding environment, but also on the timing requirements it induces. As a result, ensuring that an RTES behaves correctly is non-trivial, especially after adding time as a new dimension to the complexity of the testing process. This research addresses the problem of testing RTESs from Timed Automata (TA) specification by the following. First, a new Priority-based Approach (PA) for testing RTES modelled formally as UPPAAL timed automata (TA variant) is introduced. Test cases generated according to a proposed timed adequacy criterion (clock region coverage) are divided into three sets of priorities, namely boundary, out-boundary and in-boundary. The selection of which set is most appropriate for a System Under Test (SUT) can be decided by the tester according to the system type, time specified for the testing process and its budget. Second, PA is validated in comparison with four well-known timed testing approaches based on TA using Specification Mutation Analysis (SMA). To enable the validation, a set of timed and functional mutation operators based on TA is introduced. Three case studies are used to run SMA. The effectiveness of timed testing approaches are determined and contrasted according to the mutation score which shows that our PA achieves high mutation adequacy score compared with others. Third, to enhance the applicability of PA, a new testing tool (GeTeX) that deploys PA is introduced. In its current version, GeTeX supports Control Area Network (CAN) applications. GeTeX is validated by developing a prototype for that purpose. Using GeTeX, PA is also empirically validated in comparison with some TA testing approaches using a complete industrial-strength test bed. The assessment is based on fault coverage, structural coverage, the length of generated test cases and a proposed assessment factor. The assessment is based on fault coverage, structural coverage, the length of generated test cases and a proposed assessment factor. The assessment results confirmed the superiority of PA over the other test approaches. The overall assessment factor showed that structural and fault coverage scores of PA with respect to the length of its tests were better than the others proving the applicability of PA. Finally, an Analytical Hierarchy Process (AHP) decision-making framework for our PA is developed. The framework can provide testers with a systematic approach by which they can prioritise the available PA test sets that best fulfils their testing requirements. The AHP framework developed is based on the data collected heuristically from the test bed and data collected by interviewing testing experts. The framework is then validated using two testing scenarios. The decision outcomes of the AHP framework were significantly correlated to those of testing experts which demonstrated the soundness and validity of the framework.This study is funded by Damascus University, Syri

Analyses and optimizations of timing-constrained embedded systems considering resource synchronization and machine learning approaches

Nowadays, embedded systems have become ubiquitous, powering a vast array of applications from consumer electronics to industrial automation. Concurrently, statistical and machine learning algorithms are being increasingly adopted across various application domains, such as medical diagnosis, autonomous driving, and environmental analysis, offering sophisticated data analysis and decision-making capabilities. As the demand for intelligent and time-sensitive applications continues to surge, accompanied by growing concerns regarding data privacy, the deployment of machine learning models on embedded devices has emerged as an indispensable requirement. However, this integration introduces both significant opportunities for performance enhancement and complex challenges in deployment optimization. On the one hand, deploying machine learning models on embedded systems with limited computational capacity, power budgets, and stringent timing requirements necessitates additional adjustments to ensure optimal performance and meet the imposed timing constraints. On the other hand, the inherent capabilities of machine learning, such as self-adaptation during runtime, prove invaluable in addressing challenges encountered in embedded systems, aiding in optimization and decision-making processes. This dissertation introduces two primary modifications for the analyses and optimizations of timing-constrained embedded systems. For one thing, it addresses the relatively long access times required for shared resources of machine learning tasks. For another, it considers the limited communication resources and data privacy concerns in distributed embedded systems when deploying machine learning models. Additionally, this work provides a use case that employs a machine learning method to tackle challenges specific to embedded systems. By addressing these key aspects, this dissertation contributes to the analysis and optimization of timing-constrained embedded systems, considering resource synchronization and machine learning models to enable improved performance and efficiency in real-time applications with stringent constraints