A general framework integrating techniques for scheduling under uncertainty

Ces dernières années, de nombreux travaux de recherche ont porté sur la planification de tâches et l'ordonnancement sous incertitudes. Ce domaine de recherche comprend un large choix de modèles, techniques de résolution et systèmes, et il est difficile de les comparer car les terminologies existantes sont incomplètes. Nous avons cependant identifié des familles d'approches générales qui peuvent être utilisées pour structurer la littérature suivant trois axes perpendiculaires. Cette nouvelle structuration de l'état de l'art est basée sur la façon dont les décisions sont prises. De plus, nous proposons un modèle de génération et d'exécution pour ordonnancer sous incertitudes qui met en oeuvre ces trois familles d'approches. Ce modèle est un automate qui se développe lorsque l'ordonnancement courant n'est plus exécutable ou lorsque des conditions particulières sont vérifiées. Le troisième volet de cette thèse concerne l'étude expérimentale que nous avons menée. Au-dessus de ILOG Solver et Scheduler nous avons implémenté un prototype logiciel en C++, directement instancié de notre modèle de génération et d'exécution. Nous présentons de nouveaux problèmes d'ordonnancement probabilistes et une approche par satisfaction de contraintes combinée avec de la simulation pour les résoudre. ABSTRACT : For last years, a number of research investigations on task planning and scheduling under uncertainty have been conducted. This research domain comprises a large number of models, resolution techniques, and systems, and it is difficult to compare them since the existing terminologies are incomplete. However, we identified general families of approaches that can be used to structure the literature given three perpendicular axes. This new classification of the state of the art is based on the way decisions are taken. In addition, we propose a generation and execution model for scheduling under uncertainty that combines these three families of approaches. This model is an automaton that develops when the current schedule is no longer executable or when some particular conditions are met. The third part of this thesis concerns our experimental study. On top of ILOG Solver and Scheduler, we implemented a software prototype in C++ directly instantiated from our generation and execution model. We present new probabilistic scheduling problems and a constraintbased approach combined with simulation to solve some instances thereof

Industrial Wireless Sensor Networks

Wireless sensor networks are penetrating our daily lives, and they are starting to be deployed even in an industrial environment. The research on such industrial wireless sensor networks (IWSNs) considers more stringent requirements of robustness, reliability, and timeliness in each network layer. This Special Issue presents the recent research result on industrial wireless sensor networks. Each paper in this Special Issue has unique contributions in the advancements of industrial wireless sensor network research and we expect each paper to promote the relevant research and the deployment of IWSNs

Event and Time-Triggered Control Module Layers for Individual Robot Control Architectures of Unmanned Agricultural Ground Vehicles

Automation in the agriculture sector has increased to an extent where the accompanying methods for unmanned field management are becoming more economically viable. This manifests in the industry’s recent presentation of conceptual cab-less machines that perform all field operations under the high-level task control of a single remote operator. A dramatic change in the overall workflow for field tasks that historically assumed the presence of a human in the immediate vicinity of the work is predicted. This shift in the entire approach to farm machinery work provides producers increased control and productivity over high-level tasks and less distraction from operating individual machine actuators and implements. The final implication is decreased mechanical complexity of the cab-less field machines from their manned counter types. An Unmanned Agricultural Ground Vehicle (UAGV) electric platform received a portable control module layer (CML) which was modular and able to accept higher-level mission commands while returning system states to high-level tasks. The simplicity of this system was shown by its entire implementation running on microcontrollers networked on a Time-Triggered Controller Area Network (TTCAN) bus. A basic form of user input and output was added to the system to demonstrate a simple instance of sub-system integration. In this work, all major levels of design and implementation are examined in detail, revealing the ‘why’ and ‘how’ of each subsystem. System design philosophy is highlighted from the beginning. A state-space feedback steering controller was implemented on the machine utilizing a basic steering model found in literature. Finally, system performance is evaluated from the perspectives of a number of disciplines including: embedded systems software design, control systems, and robot control architecture. Recommendations for formalized UAGV system modeling, estimation, and control are discussed for the continuation of research in simplified low-cost machines for in-field task automation. Additional recommendations for future time-triggered CML experiments in bus robustness and redundancy are discussed. The work presented is foundational in the shift from event-triggered communications towards time-triggered CMLs for unmanned agricultural machinery and is a front-to-back demonstration of time-triggered design. Advisor: Santosh K. Pitl

Compilation de systèmes temps réel

I introduce and advocate for the concept of Real-Time Systems Compilation. By analogy with classical compilation, real-time systems compilation consists in the fully automatic construction of running, correct-by-construction implementations from functional and non-functional specifications of embedded control systems. Like in a classical compiler, the whole process must be fast (thus enabling a trial-and-error design style) and produce reasonably efficient code. This requires the use of fast heuristics, and the use of fine-grain platform and application models. Unlike a classical compiler, a real-time systems compiler must take into account non-functional properties of a system and ensure the respect of non-functional requirements (in addition to functional correctness). I also present Lopht, a real-time systems compiler for statically-scheduled real-time systems we built by combining techniques and concepts from real-time scheduling, compilation, and synchronous languages

On the use of IEEE 802.15.4/ZigBee as federating communication protocols for Wireless Sensor Networks

Tese de mestrado. Redes e Serviços de Comunicação. Faculdade de Engenharia. Universidade do Porto, Instituto Superior de Engenharia. 200

A Machine Learning Enhanced Scheme for Intelligent Network Management

The versatile networking services bring about huge influence on daily living styles while the amount and diversity of services cause high complexity of network systems. The network scale and complexity grow with the increasing infrastructure apparatuses, networking function, networking slices, and underlying architecture evolution. The conventional way is manual administration to maintain the large and complex platform, which makes effective and insightful management troublesome. A feasible and promising scheme is to extract insightful information from largely produced network data. The goal of this thesis is to use learning-based algorithms inspired by machine learning communities to discover valuable knowledge from substantial network data, which directly promotes intelligent management and maintenance. In the thesis, the management and maintenance focus on two schemes: network anomalies detection and root causes localization; critical traffic resource control and optimization. Firstly, the abundant network data wrap up informative messages but its heterogeneity and perplexity make diagnosis challenging. For unstructured logs, abstract and formatted log templates are extracted to regulate log records. An in-depth analysis framework based on heterogeneous data is proposed in order to detect the occurrence of faults and anomalies. It employs representation learning methods to map unstructured data into numerical features, and fuses the extracted feature for network anomaly and fault detection. The representation learning makes use of word2vec-based embedding technologies for semantic expression. Next, the fault and anomaly detection solely unveils the occurrence of events while failing to figure out the root causes for useful administration so that the fault localization opens a gate to narrow down the source of systematic anomalies. The extracted features are formed as the anomaly degree coupled with an importance ranking method to highlight the locations of anomalies in network systems. Two types of ranking modes are instantiated by PageRank and operation errors for jointly highlighting latent issue of locations. Besides the fault and anomaly detection, network traffic engineering deals with network communication and computation resource to optimize data traffic transferring efficiency. Especially when network traffic are constrained with communication conditions, a pro-active path planning scheme is helpful for efficient traffic controlling actions. Then a learning-based traffic planning algorithm is proposed based on sequence-to-sequence model to discover hidden reasonable paths from abundant traffic history data over the Software Defined Network architecture. Finally, traffic engineering merely based on empirical data is likely to result in stale and sub-optimal solutions, even ending up with worse situations. A resilient mechanism is required to adapt network flows based on context into a dynamic environment. Thus, a reinforcement learning-based scheme is put forward for dynamic data forwarding considering network resource status, which explicitly presents a promising performance improvement. In the end, the proposed anomaly processing framework strengthens the analysis and diagnosis for network system administrators through synthesized fault detection and root cause localization. The learning-based traffic engineering stimulates networking flow management via experienced data and further shows a promising direction of flexible traffic adjustment for ever-changing environments

Analyse et optimisation des réseaux avioniques hétérogènes

La complexité des architectures de communication avioniques ne cesse de croître avec l’augmentation du nombre des terminaux interconnectés et l’expansion de la quantité des données échangées. Afin de répondre aux besoins émergents en terme de bande passante, latence et modularité, l’architecture de communication avionique actuelle consiste à utiliser le réseau AFDX (Avionics Full DupleX Switched Ethernet) pour connecter les calculateurs et utiliser des bus d’entrée/sortie (par exemple le bus CAN (Controller Area Network)) pour connecter les capteurs et les actionneurs. Les réseaux ainsi formés sont connectés en utilisant des équipements d’interconnexion spécifiques, appelés RDC (Remote Data Concentrators) et standardisé sous la norme ARINC655. Les RDCs sont des passerelles de communication modulaires qui sont reparties dans l’avion afin de gérer l’hétérogénéité entre le réseau cœur AFDX et les bus d’entrée/sortie. Certes, les RDCs permettent d’améliorer la modularité du système avionique et de réduire le coût de sa maintenance; mais, ces équipements sont devenus un des défis majeurs durant la conception de l’architecture avionique afin de garantir les performances requises du système. Les implémentations existantes du RDC effectuent souvent une translation direct des trames et n’implémentent aucun mécanisme de gestion de ressources. Or, une utilisation efficace des ressources est un besoin important dans le contexte avionique afin de faciliter l’évolution du système et l’ajout de nouvelles fonctions. Ainsi, l’objectif de cette thèse est la conception et la validation d’un RDC optimisé implémentant des mécanismes de gestion des ressources afin d’améliorer les performances de l’architecture de communication avionique tout en respectant les contraintes temporelles du système. Afin d’atteindre cet objectif, un RDC pour les architectures réseaux de type CAN-AFDX est conçu, intégrant les fonctions suivantes: (i) groupement des trames appliqué aux flux montants, i.e., flux générés par les capteurs et destinés à l’AFDX, pour minimiser le coût des communication sur l’AFDX; (ii) la régulation des flux descendants, i.e., flux générés par des terminaux AFDX et destinés aux actionneurs, pour réduire les contentions sur le bus CAN. Par ailleurs, notre RDC permet de connecter plusieurs bus CAN à la fois tout en garantissant une isolation entre les flux. Par la suite, afin d’analyser l’impact de ce nouveau RDC sur les performances du système avionique, nous procédons à la modélisation de l’architecture CAN-AFDX, et particulièrement le RDC et ses nouvelles fonctions. Ensuite, nous introduisons une méthode d’analyse temporelle pour calculer des bornes maximales sur les délais de bout en bout et vérifier le respect des contraintes temps-réel. Plusieurs configurations du RDC peuvent répondre aux exigences du système avionique tout en offrant des économies de ressources. Nous procédons donc au paramétrage du RDC afin de minimiser la consommation de bande passante sur l’AFDX tout en respectant les contraintes temporelles. Ce problème d’optimisation est considéré comme NP-complet, et l’introduction des heuristiques adéquates s’est avérée nécessaire afin de trouver la meilleure configuration possible du RDC. Enfin, les performances de ce nouveau RDC sont validées à travers une architecture CAN-AFDX réaliste, avec plusieurs bus CAN et des centaines de flux échangés. Différents niveaux d’utilisation des bus CAN ont été considérés et les résultats obtenus ont montré l’efficacité de notre RDC à améliorer la gestion des ressources du système avionique tout en respectant les contraintes temporelles de communication. En particulier, notre RDC offre une réduction de la bande passante AFDX allant jusqu’à 40% en comparaison avec le RDC actuellement utilisé. ABSTRACT : The aim of my thesis is to provide a resources-efficient gateway to connect Input/Output (I/O) CAN buses to a backbone network based on AFDX technology, in modern avionics communication architectures. Currently, the Remote Data Concentrator (RDC) is the main standard for gateways in avionics; and the existing implementations do not integrate any resource management mechanism. To handle these limitations, we design an enhanced CAN-AFDX RDC integrating new functions: (i) Frame Packing (FP) allowing to reduce communication overheads with reference to the currently used "1 to 1" frame conversion strategy; (ii) Hierarchical Traffic Shaping (HTS) to reduce contention on the CAN bus. Furthermore, our proposed RDC allows the connection of multiple I/O CAN buses to AFDX while guaranteeing isolation between different criticality levels, using a software partitioning mechanism. To analyze the performance guarantees offered by our proposed RDC, we considered two metrics: the end-to-end latency and the induced AFDX bandwidth consumption. Furthermore, an optimization process was proposed to achieve an optimal configuration of our proposed RDC, i.e., minimizing the bandwidth utilization while meeting the real-time constraints of communication. Finally, the capacity of our proposed RDC to meet the emerging avionics requirements has been validated through a realistic avionics case study

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques