Engineering Self-Adaptive Collective Processes for Cyber-Physical Ecosystems

The pervasiveness of computing and networking is creating significant opportunities for building valuable socio-technical systems. However, the scale, density, heterogeneity, interdependence, and QoS constraints of many target systems pose severe operational and engineering challenges. Beyond individual smart devices, cyber-physical collectives can provide services or solve complex problems by leveraging a “system effect” while coordinating and adapting to context or environment change. Understanding and building systems exhibiting collective intelligence and autonomic capabilities represent a prominent research goal, partly covered, e.g., by the field of collective adaptive systems. Therefore, drawing inspiration from and building on the long-time research activity on coordination, multi-agent systems, autonomic/self-* systems, spatial computing, and especially on the recent aggregate computing paradigm, this thesis investigates concepts, methods, and tools for the engineering of possibly large-scale, heterogeneous ensembles of situated components that should be able to operate, adapt and self-organise in a decentralised fashion. The primary contribution of this thesis consists of four main parts. First, we define and implement an aggregate programming language (ScaFi), internal to the mainstream Scala programming language, for describing collective adaptive behaviour, based on field calculi. Second, we conceive of a “dynamic collective computation” abstraction, also called aggregate process, formalised by an extension to the field calculus, and implemented in ScaFi. Third, we characterise and provide a proof-of-concept implementation of a middleware for aggregate computing that enables the development of aggregate systems according to multiple architectural styles. Fourth, we apply and evaluate aggregate computing techniques to edge computing scenarios, and characterise a design pattern, called Self-organising Coordination Regions (SCR), that supports adjustable, decentralised decision-making and activity in dynamic environments.Con lo sviluppo di informatica e intelligenza artificiale, la diffusione pervasiva di device computazionali e la crescente interconnessione tra elementi fisici e digitali, emergono innumerevoli opportunità per la costruzione di sistemi socio-tecnici di nuova generazione. Tuttavia, l'ingegneria di tali sistemi presenta notevoli sfide, data la loro complessità—si pensi ai livelli, scale, eterogeneità, e interdipendenze coinvolti. Oltre a dispositivi smart individuali, collettivi cyber-fisici possono fornire servizi o risolvere problemi complessi con un “effetto sistema” che emerge dalla coordinazione e l'adattamento di componenti fra loro, l'ambiente e il contesto. Comprendere e costruire sistemi in grado di esibire intelligenza collettiva e capacità autonomiche è un importante problema di ricerca studiato, ad esempio, nel campo dei sistemi collettivi adattativi. Perciò, traendo ispirazione e partendo dall'attività di ricerca su coordinazione, sistemi multiagente e self-*, modelli di computazione spazio-temporali e, specialmente, sul recente paradigma di programmazione aggregata, questa tesi tratta concetti, metodi, e strumenti per l'ingegneria di ensemble di elementi situati eterogenei che devono essere in grado di lavorare, adattarsi, e auto-organizzarsi in modo decentralizzato. Il contributo di questa tesi consiste in quattro parti principali. In primo luogo, viene definito e implementato un linguaggio di programmazione aggregata (ScaFi), interno al linguaggio Scala, per descrivere comportamenti collettivi e adattativi secondo l'approccio dei campi computazionali. In secondo luogo, si propone e caratterizza l'astrazione di processo aggregato per rappresentare computazioni collettive dinamiche concorrenti, formalizzata come estensione al field calculus e implementata in ScaFi. Inoltre, si analizza e implementa un prototipo di middleware per sistemi aggregati, in grado di supportare più stili architetturali. Infine, si applicano e valutano tecniche di programmazione aggregata in scenari di edge computing, e si propone un pattern, Self-Organising Coordination Regions, per supportare, in modo decentralizzato, attività decisionali e di regolazione in ambienti dinamici

Software engineering perspectives on physiological computing

Physiological computing is an interesting and promising concept to widen the communication channel between the (human) users and computers, thus allowing an increase of software systems' contextual awareness and rendering software systems smarter than they are today. Using physiological inputs in pervasive computing systems allows re-balancing the information asymmetry between the human user and the computer system: while pervasive computing systems are well able to flood the user with information and sensory input (such as sounds, lights, and visual animations), users only have a very narrow input channel to computing systems; most of the time, restricted to keyboards, mouse, touchscreens, accelerometers and GPS receivers (through smartphone usage, e.g.). Interestingly, this information asymmetry often forces the user to subdue to the quirks of the computing system to achieve his goals -- for example, users may have to provide information the software system demands through a narrow, time-consuming input mode that the system could sense implicitly from the human body. Physiological computing is a way to circumvent these limitations; however, systematic means for developing and moulding physiological computing applications into software are still unknown. This thesis proposes a methodological approach to the creation of physiological computing applications that makes use of component-based software engineering. Components help imposing a clear structure on software systems in general, and can thus be used for physiological computing systems as well. As an additional bonus, using components allow physiological computing systems to leverage reconfigurations as a means to control and adapt their own behaviours. This adaptation can be used to adjust the behaviour both to the human and to the available computing environment in terms of resources and available devices - an activity that is crucial for complex physiological computing systems. With the help of components and reconfigurations, it is possible to structure the functionality of physiological computing applications in a way that makes them manageable and extensible, thus allowing a stepwise and systematic extension of a system's intelligence. Using reconfigurations entails a larger issue, however. Understanding and fully capturing the behaviour of a system under reconfiguration is challenging, as the system may change its structure in ways that are difficult to fully predict. Therefore, this thesis also introduces a means for formal verification of reconfigurations based on assume-guarantee contracts. With the proposed assume-guarantee contract framework, it is possible to prove that a given system design (including component behaviours and reconfiguration specifications) is satisfying real-time properties expressed as assume-guarantee contracts using a variant of real-time linear temporal logic introduced in this thesis - metric interval temporal logic for reconfigurable systems. Finally, this thesis embeds both the practical approach to the realisation of physiological computing systems and formal verification of reconfigurations into Scrum, a modern and agile software development methodology. The surrounding methodological approach is intended to provide a frame for the systematic development of physiological computing systems from first psychological findings to a working software system with both satisfactory functionality and software quality aspects. By integrating practical and theoretical aspects of software engineering into a self-contained development methodology, this thesis proposes a roadmap and guidelines for the creation of new physiological computing applications.Physiologisches Rechnen ist ein interessantes und vielversprechendes Konzept zur Erweiterung des Kommunikationskanals zwischen (menschlichen) Nutzern und Rechnern, und dadurch die Berücksichtigung des Nutzerkontexts in Software-Systemen zu verbessern und damit Software-Systeme intelligenter zu gestalten, als sie es heute sind. Physiologische Eingangssignale in ubiquitären Rechensystemen zu verwenden, ermöglicht eine Neujustierung der Informationsasymmetrie, die heute zwischen Menschen und Rechensystemen existiert: Während ubiquitäre Rechensysteme sehr wohl in der Lage sind, den Menschen mit Informationen und sensorischen Reizen zu überfluten (z.B. durch Töne, Licht und visuelle Animationen), hat der Mensch nur sehr begrenzte Einflussmöglichkeiten zu Rechensystemen. Meistens stehen nur Tastaturen, die Maus, berührungsempfindliche Bildschirme, Beschleunigungsmesser und GPS-Empfänger (zum Beispiel durch Mobiltelefone oder digitale Assistenten) zur Verfügung. Diese Informationsasymmetrie zwingt die Benutzer zur Unterwerfung unter die Usancen der Rechensysteme, um ihre Ziele zu erreichen - zum Beispiel müssen Nutzer Daten manuell eingeben, die auch aus Sensordaten des menschlichen Körpers auf unauffällige weise erhoben werden können. Physiologisches Rechnen ist eine Möglichkeit, diese Beschränkung zu umgehen. Allerdings fehlt eine systematische Methodik für die Entwicklung physiologischer Rechensysteme bis zu fertiger Software. Diese Dissertation präsentiert einen methodischen Ansatz zur Entwicklung physiologischer Rechenanwendungen, der auf der komponentenbasierten Softwareentwicklung aufbaut. Der komponentenbasierte Ansatz hilft im Allgemeinen dabei, eine klare Architektur des Software-Systems zu definieren, und kann deshalb auch für physiologische Rechensysteme angewendet werden. Als zusätzlichen Vorteil erlaubt die Komponentenorientierung in physiologischen Rechensystemen, Rekonfigurationen als Mittel zur Kontrolle und Anpassung des Verhaltens von physiologischen Rechensystemen zu verwenden. Diese Adaptionstechnik kann genutzt werden um das Verhalten von physiologischen Rechensystemen an den Benutzer anzupassen, sowie an die verfügbare Recheninfrastruktur im Sinne von Systemressourcen und Geräten - eine Maßnahme, die in komplexen physiologischen Rechensystemen entscheidend ist. Mit Hilfe der Komponentenorientierung und von Rekonfigurationen wird es möglich, die Funktionalität von physiologischen Rechensystemen so zu strukturieren, dass das System wartbar und erweiterbar bleibt. Dadurch wird eine schrittweise und systematische Erweiterung der Funktionalität des Systems möglich. Die Verwendung von Rekonfigurationen birgt allerdings Probleme. Das Systemverhalten eines Software-Systems, das Rekonfigurationen unterworfen ist zu verstehen und vollständig einzufangen ist herausfordernd, da das System seine Struktur auf schwer vorhersehbare Weise verändern kann. Aus diesem Grund führt diese Arbeit eine Methode zur formalen Verifikation von Rekonfigurationen auf Grundlage von Annahme-Zusicherungs-Verträgen ein. Mit dem vorgeschlagenen Annahme-Zusicherungs-Vertragssystem ist es möglich zu beweisen, dass ein gegebener Systementwurf (mitsamt Komponentenverhalten und Spezifikation des Rekonfigurationsverhaltens) eine als Annahme-Zusicherungs-Vertrag spezifizierte Echtzeiteigenschaft erfüllt. Für die Spezifikation von Echtzeiteigenschaften kann eine Variante von linearer Temporallogik für Echtzeit verwendet werden, die in dieser Arbeit eingeführt wird: Die metrische Intervall-Temporallogik für rekonfigurierbare Systeme. Schließlich wird in dieser Arbeit sowohl ein praktischer Ansatz zur Realisierung von physiologischen Rechensystemen als auch die formale Verifikation von Rekonfigurationen in Scrum eingebettet, einer modernen und agilen Softwareentwicklungsmethodik. Der methodische Ansatz bietet einen Rahmen für die systematische Entwicklung physiologischer Rechensysteme von Erkenntnissen zur menschlichen Physiologie hin zu funktionierenden physiologischen Softwaresystemen mit zufriedenstellenden funktionalen und qualitativen Eigenschaften. Durch die Integration sowohl von praktischen wie auch theoretischen Aspekten der Softwaretechnik in eine vollständige Entwicklungsmethodik bietet diese Arbeit einen Fahrplan und Richtlinien für die Erstellung neuer physiologischer Rechenanwendungen

Model for WCET prediction, scheduling and task allocation for emergent agent-behaviours in real-time scenarios

[ES]Hasta el momento no se conocen modelos de tiempo real específicamente desarrollados para su uso en sistemas abiertos, como las Organizaciones Virtuales de Agentes (OVs). Convencionalmente, los modelos de tiempo real se aplican a sistemas cerrados donde todas las variables se conocen a priori. Esta tesis presenta nuevas contribuciones y la novedosa integración de agentes en tiempo real dentro de OVs. Hasta donde alcanza nuestro conocimiento, éste es el primer modelo específicamente diseñado para su aplicación en OVs con restricciones temporales estrictas. Esta tesis proporciona una nueva perspectiva que combina la apertura y dinamicidad necesarias en una OV con las restricciones de tiempo real. Ésto es una aspecto complicado ya que el primer paradigma no es estricto, como el propio término de sistema abierto indica, sin embargo, el segundo paradigma debe cumplir estrictas restricciones. En resumen, el modelo que se presenta permite definir las acciones que una OV debe llevar a cabo con un plazo concreto, considerando los cambios que pueden ocurrir durante la ejecución de un plan particular. Es una planificación de tiempo real en una OV. Otra de las principales contribuciones de esta tesis es un modelo para el cálculo del tiempo de ejecución en el peor caso (WCET). La propuesta es un modelo efectivo para calcular el peor escenario cuando un agente desea formar parte de una OV y para ello, debe incluir sus tareas o comportamientos dentro del sistema de tiempo real, es decir, se calcula el WCET de comportamientos emergentes en tiempo de ejecución. También se incluye una planificación local para cada nodo de ejecución basada en el algoritmo FPS y una distribución de tareas entre los nodos disponibles en el sistema. Para ambos modelos se usan modelos matemáticos y estadísticos avanzados para crear un mecanismo adaptable, robusto y eficiente para agentes inteligentes en OVs. El desconocimiento, pese al estudio realizado, de una plataforma para sistemas abiertos que soporte agentes con restricciones de tiempo real y los mecanismos necesarios para el control y la gestión de OVs, es la principal motivación para el desarrollo de la plataforma de agentes PANGEA+RT. PANGEA+RT es una innovadora plataforma multi-agente que proporciona soporte para la ejecución de agentes en ambientes de tiempo real. Finalmente, se presenta un caso de estudio donde robots heterogéneos colaboran para realizar tareas de vigilancia. El caso de estudio se ha desarrollado con la plataforma PANGEA+RT donde el modelo propuesto está integrado. Por tanto al final de la tesis, con este caso de estudio se obtienen los resultados y conclusiones que validan el modelo

From distributed coordination to field calculus and aggregate computing

open6siThis work has been partially supported by: EU Horizon 2020 project HyVar (www.hyvar-project .eu), GA No. 644298; ICT COST Action IC1402 ARVI (www.cost -arvi .eu); Ateneo/CSP D16D15000360005 project RunVar (runvar-project.di.unito.it).Aggregate computing is an emerging approach to the engineering of complex coordination for distributed systems, based on viewing system interactions in terms of information propagating through collectives of devices, rather than in terms of individual devices and their interaction with their peers and environment. The foundation of this approach is the distillation of a number of prior approaches, both formal and pragmatic, proposed under the umbrella of field-based coordination, and culminating into the field calculus, a universal functional programming model for the specification and composition of collective behaviours with equivalent local and aggregate semantics. This foundation has been elaborated into a layered approach to engineering coordination of complex distributed systems, building up to pragmatic applications through intermediate layers encompassing reusable libraries of program components. Furthermore, some of these components are formally shown to satisfy formal properties like self-stabilisation, which transfer to whole application services by functional composition. In this survey, we trace the development and antecedents of field calculus, review the field calculus itself and the current state of aggregate computing theory and practice, and discuss a roadmap of current research directions with implications for the development of a broad range of distributed systems.embargoed_20210910Viroli, Mirko; Beal, Jacob; Damiani, Ferruccio; Audrito, Giorgio; Casadei, Roberto; Pianini, DaniloViroli, Mirko; Beal, Jacob; Damiani, Ferruccio; Audrito, Giorgio; Casadei, Roberto; Pianini, Danil

Methodology for Testing RFID Applications

Radio Frequency Identification (RFID) is a promising technology for process automation and beyond that capable of identifying objects without the need for a line-of-sight. However, the trend towards automatic identification of objects also increases the demand for high quality RFID applications. Therefore, research on testing RFID systems and methodical approaches for testing are needed. This thesis presents a novel methodology for the system level test of RFID applications. The approach called ITERA, allows for the automatic generation of tests, defines a semantic model of the RFID system and provides a test environment for RFID applications. The method introduced can be used to gradually transform use cases into a semi-formal test specification. Test cases are then systematically generated, in order to execute them in the test environment. It applies the principle of model based testing from a black-box perspective in combination with a virtual environment for automatic test execution. The presence of RFID tags in an area, monitored by an RFID reader, can be modelled by time-based sets using set-theory and discrete events. Furthermore, the proposed description and semantics can be used to specify RFID systems and their applications, which might also be used for other purposes than testing. The approach uses the Unified Modelling Language to model the characteristics of the system under test. Based on the ITERA meta model test execution paths are extracted directly from activity diagrams and RFID specific test cases are generated. The approach introduced in this thesis allows to reduce the efforts for RFID application testing by systematically generating test cases and the automatic test execution. In combination with meta model and by considering additional parameters, like unreliability factors, it not only satisfies functional testing aspects, but also increases the confidence in the robustness of the tested application. Mixed with the instantly available virtual readers, it has the potential to speed up the development process and decrease the costs - even during the early development phases. ITERA can be used for highly automated testing, reproducible tests and because of the instantly available readers, even before the real environment is deployed. Furthermore, the total control of the RFID environment enables to test applications which might be difficult to test manually. This thesis will explain the motivation and objectives of this new RFID application test methodology. Based on a RFID system analysis it proposes a practical solution on the identified issues. Further, it gives a literature review on testing fundamentals, model based test case generation, the typical components of a RFID system and RFID standards used in industry.Integrative Test-Methodology for RFID Applications (ITERA) - Project: Eurostars!5516 ITERA, FKZ 01QE1105

A Contribution to Resource-Aware Architectures for Humanoid Robots

The goal of this work is to provide building blocks for resource-aware robot architectures. The topic of these blocks are data-driven generation of context-sensitive resource models, prediction of future resource utilizations, and resource-aware computer vision and motion planning algorithms. The implementation of these algorithms is based on resource-aware concepts and methodologies originating from the Transregional Collaborative Research Center "Invasive Computing" (SFB/TR 89)

Simulation Tools for the Study of the Interaction between Communication and Action in Cognitive Robots

In this thesis I report the development of FARSA (Framework for Autonomous Robotics Simulation and Analysis), a simulation tool for the study of the interaction between language and action in cognitive robots and more in general for experiments in embodied cognitive science. Before presenting the tools, I will describe a series of experiments that involve simulated humanoid robots that acquire their behavioural and language skills autonomously through a trial-and-error adaptive process in which random variations of the free parameters of the robots’ controller are retained or discarded on the basis of their effect on the overall behaviour exhibited by the robot in interaction with the environment. More specifically the first series of experiments shows how the availability of linguistic stimuli provided by a caretaker, that indicate the elementary actions that need to be carried out in order to accomplish a certain complex action, facilitates the acquisition of the required behavioural capacity. The second series of experiments shows how a robot trained to comprehend a set of command phrases by executing the corresponding appropriate behaviour can generalize its knowledge by comprehending new, never experienced sentences, and by producing new appropriate actions. Together with their scientific relevance, these experiments provide a series of requirements that have been taken into account during the development of FARSA. The objective of this project is that to reduce the complexity barrier that currently discourages part of the researchers interested in the study of behaviour and cognition from initiating experimental activity in this area. FARSA is the only available tools that provide an integrated framework for carrying on experiments of this type, i.e. it is the only tool that provides ready to use integrated components that enable to define the characteristics of the robots and of the environment, the characteristics of the robots’ controller, and the characteristics of the adaptive process. Overall this enables users to quickly setup experiments, including complex experiments, and to quickly start collecting results

Mapping the big data landscape: technologies, platforms and paradigms for real-time analytics of data streams

The ‘Big Data’ of yesterday is the ‘data’ of today. As technology progresses, new challenges arise and new solutions are developed. Due to the emergence of Internet of Things applications within the last decade, the field of Data Mining has been faced with the challenge of processing and analysing data streams in real-time, and under high data throughput conditions. This is often referred to as the Velocity aspect of Big Data. Whereas there are numerous reviews on Data Stream Mining techniques and applications, there is very little work surveying Data Stream processing paradigms and associated technologies, from data collection through to pre-processing and feature processing, from the perspective of the user, not that of the service provider. In this paper, we evaluate a particular type of solution, which focuses on streaming data, and processing pipelines that permit online analysis of data streams that cannot be stored as-is on the computing platform. We review foundational computational concepts such as distributed computation, fault-tolerant computing, and computational paradigms/architectures. We then review the available technological solutions, and applications that pertain to data stream mining as case studies of these theoretical concepts. We conclude with a discussion of the field of data stream processing/analytics, future directions and research challenges

Accessible Integration of Physiological Adaptation in Human-Robot Interaction

Technological advancements in creating and commercializing novel unobtrusive wearable physiological sensors have generated new opportunities to develop adaptive human-robot interaction (HRI). Detecting complex human states such as engagement and stress when interacting with social agents could bring numerous advantages to creating meaningful interactive experiences. Bodily signals have classically been used for post-interaction analysis in HRI. Despite this, real-time measurements of autonomic responses have been used in other research domains to develop physiologically adaptive systems with great success; increasing user-experience, task performance, and reducing cognitive workload. This thesis presents the HRI Physio Lib, a conceptual framework, and open-source software library to facilitate the development of physiologically adaptive HRI scenarios. Both the framework and architecture of the library are described in-depth, along with descriptions of additional software tools that were developed to make the inclusion of physiological signals easier for robotics frameworks. The framework is structured around four main components for designing physiologically adaptive experimental scenarios: signal acquisition, processing and analysis; social robot and communication; and scenario and adaptation. Open-source software tools have been developed to assist in the individual creation of each described component. To showcase our framework and test the software library, we developed, as a proof-of-concept, a simple scenario revolving around a physiologically aware exercise coach, that modulates the speed and intensity of the activity to promote an effective cardiorespiratory exercise. We employed the socially assistive QT robot for our exercise scenario, as it provides a comprehensive ROS interface, making prototyping of behavioral responses fast and simple. Our exercise routine was designed following guidelines by the American College of Sports Medicine. We describe our physiologically adaptive algorithm and propose an alternative second one with stochastic elements. Finally, a discussion about other HRI domains where the addition of a physiologically adaptive mechanism could result in novel advances in interaction quality is provided as future extensions for this work. From the literature, we identified improving engagement, providing deeper social connections, health care scenarios, and also applications for self-driving vehicles as promising avenues for future research where a physiologically adaptive social robot could improve user experience

Toward Software-Defined Networking-Based IoT Frameworks: A Systematic Literature Review, Taxonomy, Open Challenges and Prospects

Internet of Things (IoT) is characterized as one of the leading actors for the next evolutionary stage in the computing world. IoT-based applications have already produced a plethora of novel services and are improving the living standard by enabling innovative and smart solutions. However, along with its rapid adoption, IoT technology also creates complex challenges regarding the management of IoT networks due to its resource limitations (computational power, energy, and security). Hence, it is urgently needed to refine the IoT-based application’s architectures to robustly manage the overall IoT infrastructure. Software-defined networking (SDN) has emerged as a paradigm that offers software-based controllers to manage hardware infrastructure and traffic flow on a network effectively. SDN architecture has the potential to provide efficient and reliable IoT network management. This research provides a comprehensive survey investigating the published studies on SDN-based frameworks to address IoT management issues in the dimensions of fault tolerance, energy management, scalability, load balancing, and security service provisioning within the IoT networks. We conducted a Systematic Literature Review (SLR) on the research studies (published from 2010 to 2022) focusing on SDN-based IoT management frameworks. We provide an extensive discussion on various aspects of SDN-based IoT solutions and architectures. We elaborate a taxonomy of the existing SDN-based IoT frameworks and solutions by classifying them into categories such as network function virtualization, middleware, OpenFlow adaptation, and blockchain-based management. We present the research gaps by identifying and analyzing the key architectural requirements and management issues in IoT infrastructures. Finally, we highlight various challenges and a range of promising opportunities for future research to provide a roadmap for addressing the weaknesses and identifying the benefits from the potentials offered by SDN-based IoT solutions