Carbon Catcher Design Report

Overview. The design of the overall Carbon Catcher project can be separated into four distinct systems, each of which is assigned a specialized committee. The committee names and responsibilities are listed below: Air Mover The overall goal for the Air Mover committee is the design of the turbine assembly. As the overall goal of the project is to collect and separate carbon dioxide from the air, one of the most important parts is to actually get the air to pass through the carbon-catching membrane. Passive air would not give a significant enough yield rate to make the carbon dioxide collection rate impactful, thus air must be sucked through a vacuum/turbine. Membrane The goal of Membrain is to create a membrane that can filter out CO2 through various methods. These methods are limited, due to there being such variety, to certain techniques and membrane material types that have been decided, prior, by the committee. Most membranes will be geared towards utilizing temperature and pressure along with gaseous speed and flow rate. In addition, examining certain treatments, such as regeneration of material, and replacements will be looked into as well, to see how it fares in sustainability. Carbon Storer The Carbon Storer committee will design a store and transport system for fluid CO2 after it is extracted from the atmosphere. Primary considerations include geological solutions, cost-effective materials, and analysis methods to improve overall capacity and efficiency. Additionally, the committee will select an environmentally and economically sustainable method of recycling the captured CO2. PyControl The PyControl committee will design a series of sensors and actuators, which will primarily support the sequestration and pipeline systems present in the Carbon Storer Committee and direct air capture system in Air Mover. The design can be broken into four control layers: Input/Output, Field Controllers, Data, and Supervisory. Goal The overarching goal of Carbon Catcher is to design a cost-effective, scalable atmospheric carbon dioxide removal system that is capable of being deployed in a variety of urban environments and may fit a variety of different customer requirements or requests

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Defining Service Level Agreements in Serverless Computing

The emergence of serverless computing has brought significant advancements to the delivery of computing resources to cloud users. With the abstraction of infrastructure, ecosystem, and execution environments, users could focus on their code while relying on the cloud provider to manage the abstracted layers. In addition, desirable features such as autoscaling and high availability became a provider’s responsibility and can be adopted by the user\u27s application at no extra overhead. Despite such advancements, significant challenges must be overcome as applications transition from monolithic stand-alone deployments to the ephemeral and stateless microservice model of serverless computing. These challenges pertain to the uniqueness of the conceptual and implementation models of serverless computing. One of the notable challenges is the complexity of defining Service Level Agreements (SLA) for serverless functions. As the serverless model shifts the administration of resources, ecosystem, and execution layers to the provider, users become mere consumers of the provider’s abstracted platform with no insight into its performance. Suboptimal conditions of the abstracted layers are not visible to the end-user who has no means to assess their performance. Thus, SLA in serverless computing must take into consideration the unique abstraction of its model. This work investigates the Service Level Agreement (SLA) modeling of serverless functions\u27 and serverless chains’ executions. We highlight how serverless SLA fundamentally differs from earlier cloud delivery models. We then propose an approach to define SLA for serverless functions by utilizing resource utilization fingerprints for functions\u27 executions and a method to assess if executions adhere to that SLA. We evaluate the approach’s accuracy in detecting SLA violations for a broad range of serverless application categories. Our validation results illustrate a high accuracy in detecting SLA violations resulting from resource contentions and provider’s ecosystem degradations. We conclude by presenting the empirical validation of our proposed approach, which could detect Execution-SLA violations with accuracy up to 99%

Designing and Deploying Internet of Things Applications in the Industry: An Empirical Investigation

RÉSUMÉ : L’Internet des objets (IdO) a pour objectif de permettre la connectivité à presque tous les objets trouvés dans l’espace physique. Il étend la connectivité aux objets de tous les jours et o˙re la possibilité de surveiller, de suivre, de se connecter et d’intéragir plus eÿcacement avec les actifs industriels. Dans l’industrie de nos jours, les réseaux de capteurs connectés surveillent les mouvements logistiques, fabriquent des machines et aident les organisations à améliorer leur eÿcacité et à réduire les coûts. Cependant, la conception et l’implémentation d’un réseau IdO restent, aujourd’hui, une tâche particulièrement diÿcile. Nous constatons un haut niveau de fragmentation dans le paysage de l’IdO, les développeurs se complaig-nent régulièrement de la diÿculté à intégrer diverses technologies avec des divers objets trouvés dans les systèmes IdO et l’absence des directives et/ou des pratiques claires pour le développement et le déploiement d’application IdO sûres et eÿcaces. Par conséquent, analyser et comprendre les problèmes liés au développement et au déploiement de l’IdO sont primordiaux pour permettre à l’industrie d’exploiter son plein potentiel. Dans cette thèse, nous examinons les interactions des spécialistes de l’IdO sur le sites Web populaire, Stack Overflow et Stack Exchange, afin de comprendre les défis et les problèmes auxquels ils sont confrontés lors du développement et du déploiement de di˙érentes appli-cations de l’IdO. Ensuite, nous examinons le manque d’interopérabilité entre les techniques développées pour l’IdO, nous étudions les défis que leur intégration pose et nous fournissons des directives aux praticiens intéressés par la connexion des réseaux et des dispositifs de l’IdO pour développer divers services et applications. D’autre part, la sécurité étant essen-tielle au succès de cette technologie, nous étudions les di˙érentes menaces et défis de sécurité sur les di˙érentes couches de l’architecture des systèmes de l’IdO et nous proposons des contre-mesures. Enfin, nous menons une série d’expériences qui vise à comprendre les avantages et les incon-vénients des déploiements ’serverful’ et ’serverless’ des applications de l’IdO afin de fournir aux praticiens des directives et des recommandations fondées sur des éléments probants relatifs à de tels déploiements. Les résultats présentés représentent une étape très importante vers une profonde compréhension de ces technologies très prometteuses. Nous estimons que nos recommandations et nos suggestions aideront les praticiens et les bâtisseurs technologiques à améliorer la qualité des logiciels et des systèmes de l’IdO. Nous espérons que nos résultats pourront aider les communautés et les consortiums de l’IdO à établir des normes et des directives pour le développement, la maintenance, et l’évolution des logiciels de l’IdO.----------ABSTRACT : Internet of Things (IoT) aims to bring connectivity to almost every object found in the phys-ical space. It extends connectivity to everyday things, opens up the possibility to monitor, track, connect, and interact with industrial assets more eÿciently. In the industry nowadays, we can see connected sensor networks monitor logistics movements, manufacturing machines, and help organizations improve their eÿciency and reduce costs as well. However, designing and implementing an IoT network today is still a very challenging task. We are witnessing a high level of fragmentation in the IoT landscape and developers regularly complain about the diÿculty to integrate diverse technologies of various objects found in IoT systems, and the lack of clear guidelines and–or practices for developing and deploying safe and eÿcient IoT applications. Therefore, analyzing and understanding issues related to the development and deployment of the Internet of Things is utterly important to allow the industry to utilize its fullest potential. In this thesis, we examine IoT practitioners’ discussions on the popular Q&A websites, Stack Overflow and Stack Exchange, to understand the challenges and issues that they face when developing and deploying di˙erent IoT applications. Next, we examine the lack of interoper-ability among technologies developed for IoT and study the challenges that their integration poses and provide guidelines for practitioners interested in connecting IoT networks and de-vices to develop various services and applications. Since security issues are center to the success of this technology, we also investigate di˙erent security threats and challenges across di˙erent layers of the architecture of IoT systems and propose countermeasures. Finally, we conduct a series of experiments to understand the advantages and trade-o˙s of serverful and serverless deployments of IoT applications in order to provide practitioners with evidence-based guidelines and recommendations on such deployments. The results presented in this thesis represent a first important step towards a deep understanding of these very promising technologies. We believe that our recommendations and suggestions will help practitioners and technology builders improve the quality of IoT software and systems. We also hope that our results can help IoT communities and consortia establish standards and guidelines for the development, maintenance, and evolution of IoT software and systems