A Survey on Data Plane Programming with P4: Fundamentals, Advances, and Applied Research

With traditional networking, users can configure control plane protocols to match the specific network configuration, but without the ability to fundamentally change the underlying algorithms. With SDN, the users may provide their own control plane, that can control network devices through their data plane APIs. Programmable data planes allow users to define their own data plane algorithms for network devices including appropriate data plane APIs which may be leveraged by user-defined SDN control. Thus, programmable data planes and SDN offer great flexibility for network customization, be it for specialized, commercial appliances, e.g., in 5G or data center networks, or for rapid prototyping in industrial and academic research. Programming protocol-independent packet processors (P4) has emerged as the currently most widespread abstraction, programming language, and concept for data plane programming. It is developed and standardized by an open community and it is supported by various software and hardware platforms. In this paper, we survey the literature from 2015 to 2020 on data plane programming with P4. Our survey covers 497 references of which 367 are scientific publications. We organize our work into two parts. In the first part, we give an overview of data plane programming models, the programming language, architectures, compilers, targets, and data plane APIs. We also consider research efforts to advance P4 technology. In the second part, we analyze a large body of literature considering P4-based applied research. We categorize 241 research papers into different application domains, summarize their contributions, and extract prototypes, target platforms, and source code availability.Comment: Submitted to IEEE Communications Surveys and Tutorials (COMS) on 2021-01-2

New Fault Detection, Mitigation and Injection Strategies for Current and Forthcoming Challenges of HW Embedded Designs

Tesis por compendio[EN] Relevance of electronics towards safety of common devices has only been growing, as an ever growing stake of the functionality is assigned to them. But of course, this comes along the constant need for higher performances to fulfill such functionality requirements, while keeping power and budget low. In this scenario, industry is struggling to provide a technology which meets all the performance, power and price specifications, at the cost of an increased vulnerability to several types of known faults or the appearance of new ones. To provide a solution for the new and growing faults in the systems, designers have been using traditional techniques from safety-critical applications, which offer in general suboptimal results. In fact, modern embedded architectures offer the possibility of optimizing the dependability properties by enabling the interaction of hardware, firmware and software levels in the process. However, that point is not yet successfully achieved. Advances in every level towards that direction are much needed if flexible, robust, resilient and cost effective fault tolerance is desired. The work presented here focuses on the hardware level, with the background consideration of a potential integration into a holistic approach. The efforts in this thesis have focused several issues: (i) to introduce additional fault models as required for adequate representativity of physical effects blooming in modern manufacturing technologies, (ii) to provide tools and methods to efficiently inject both the proposed models and classical ones, (iii) to analyze the optimum method for assessing the robustness of the systems by using extensive fault injection and later correlation with higher level layers in an effort to cut development time and cost, (iv) to provide new detection methodologies to cope with challenges modeled by proposed fault models, (v) to propose mitigation strategies focused towards tackling such new threat scenarios and (vi) to devise an automated methodology for the deployment of many fault tolerance mechanisms in a systematic robust way. The outcomes of the thesis constitute a suite of tools and methods to help the designer of critical systems in his task to develop robust, validated, and on-time designs tailored to his application.[ES] La relevancia que la electrónica adquiere en la seguridad de los productos ha crecido inexorablemente, puesto que cada vez ésta copa una mayor influencia en la funcionalidad de los mismos. Pero, por supuesto, este hecho viene acompañado de una necesidad constante de mayores prestaciones para cumplir con los requerimientos funcionales, al tiempo que se mantienen los costes y el consumo en unos niveles reducidos. En este escenario, la industria está realizando esfuerzos para proveer una tecnología que cumpla con todas las especificaciones de potencia, consumo y precio, a costa de un incremento en la vulnerabilidad a múltiples tipos de fallos conocidos o la introducción de nuevos. Para ofrecer una solución a los fallos nuevos y crecientes en los sistemas, los diseñadores han recurrido a técnicas tradicionalmente asociadas a sistemas críticos para la seguridad, que ofrecen en general resultados sub-óptimos. De hecho, las arquitecturas empotradas modernas ofrecen la posibilidad de optimizar las propiedades de confiabilidad al habilitar la interacción de los niveles de hardware, firmware y software en el proceso. No obstante, ese punto no está resulto todavía. Se necesitan avances en todos los niveles en la mencionada dirección para poder alcanzar los objetivos de una tolerancia a fallos flexible, robusta, resiliente y a bajo coste. El trabajo presentado aquí se centra en el nivel de hardware, con la consideración de fondo de una potencial integración en una estrategia holística. Los esfuerzos de esta tesis se han centrado en los siguientes aspectos: (i) la introducción de modelos de fallo adicionales requeridos para la representación adecuada de efectos físicos surgentes en las tecnologías de manufactura actuales, (ii) la provisión de herramientas y métodos para la inyección eficiente de los modelos propuestos y de los clásicos, (iii) el análisis del método óptimo para estudiar la robustez de sistemas mediante el uso de inyección de fallos extensiva, y la posterior correlación con capas de más alto nivel en un esfuerzo por recortar el tiempo y coste de desarrollo, (iv) la provisión de nuevos métodos de detección para cubrir los retos planteados por los modelos de fallo propuestos, (v) la propuesta de estrategias de mitigación enfocadas hacia el tratamiento de dichos escenarios de amenaza y (vi) la introducción de una metodología automatizada de despliegue de diversos mecanismos de tolerancia a fallos de forma robusta y sistemática. Los resultados de la presente tesis constituyen un conjunto de herramientas y métodos para ayudar al diseñador de sistemas críticos en su tarea de desarrollo de diseños robustos, validados y en tiempo adaptados a su aplicación.[CA] La rellevància que l'electrònica adquireix en la seguretat dels productes ha crescut inexorablement, puix cada volta més aquesta abasta una major influència en la funcionalitat dels mateixos. Però, per descomptat, aquest fet ve acompanyat d'un constant necessitat de majors prestacions per acomplir els requeriments funcionals, mentre es mantenen els costos i consums en uns nivells reduïts. Donat aquest escenari, la indústria està fent esforços per proveir una tecnologia que complisca amb totes les especificacions de potència, consum i preu, tot a costa d'un increment en la vulnerabilitat a diversos tipus de fallades conegudes, i a la introducció de nous tipus. Per oferir una solució a les noves i creixents fallades als sistemes, els dissenyadors han recorregut a tècniques tradicionalment associades a sistemes crítics per a la seguretat, que en general oferixen resultats sub-òptims. De fet, les arquitectures empotrades modernes oferixen la possibilitat d'optimitzar les propietats de confiabilitat en habilitar la interacció dels nivells de hardware, firmware i software en el procés. Tot i això eixe punt no està resolt encara. Es necessiten avanços a tots els nivells en l'esmentada direcció per poder assolir els objectius d'una tolerància a fallades flexible, robusta, resilient i a baix cost. El treball ací presentat se centra en el nivell de hardware, amb la consideració de fons d'una potencial integració en una estratègia holística. Els esforços d'esta tesi s'han centrat en els següents aspectes: (i) la introducció de models de fallada addicionals requerits per a la representació adequada d'efectes físics que apareixen en les tecnologies de fabricació actuals, (ii) la provisió de ferramentes i mètodes per a la injecció eficient del models proposats i dels clàssics, (iii) l'anàlisi del mètode òptim per estudiar la robustesa de sistemes mitjançant l'ús d'injecció de fallades extensiva, i la posterior correlació amb capes de més alt nivell en un esforç per retallar el temps i cost de desenvolupament, (iv) la provisió de nous mètodes de detecció per cobrir els reptes plantejats pels models de fallades proposats, (v) la proposta d'estratègies de mitigació enfocades cap al tractament dels esmentats escenaris d'amenaça i (vi) la introducció d'una metodologia automatitzada de desplegament de diversos mecanismes de tolerància a fallades de forma robusta i sistemàtica. Els resultats de la present tesi constitueixen un conjunt de ferramentes i mètodes per ajudar el dissenyador de sistemes crítics en la seua tasca de desenvolupament de dissenys robustos, validats i a temps adaptats a la seua aplicació.Espinosa García, J. (2016). New Fault Detection, Mitigation and Injection Strategies for Current and Forthcoming Challenges of HW Embedded Designs [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/73146TESISCompendi

Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in Africa

With growing machine learning (ML) applications in healthcare, there have been calls for fairness in ML to understand and mitigate ethical concerns these systems may pose. Fairness has implications for global health in Africa, which already has inequitable power imbalances between the Global North and South. This paper seeks to explore fairness for global health, with Africa as a case study. We propose fairness attributes for consideration in the African context and delineate where they may come into play in different ML-enabled medical modalities. This work serves as a basis and call for action for furthering research into fairness in global health

The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed

Enabling Richer Insight Into Runtime Executions Of Systems

Systems software of very large scales are being heavily used today in various important scenarios such as online retail, banking, content services, web search and social networks. As the scale of functionality and complexity grows in these software, managing the implementations becomes a considerable challenge for developers, designers and maintainers. Software needs to be constantly monitored and tuned for optimal efficiency and user satisfaction. With large scale, these systems incorporate significant degrees of asynchrony, parallelism and distributed executions, reducing the manageability of software including performance management. Adding to the complexity, developers are under pressure between developing new functionality for customers and maintaining existing programs. This dissertation argues that the manual effort currently required to manage performance of these systems is very high, and can be automated to both reduce the likelihood of problems and quickly fix them once identified. The execution logs from these systems are easily available and provide rich information about the internals at runtime for diagnosis purposes, but the volume of logs is simply too large for today\u27s techniques. Developers hence spend many human hours observing and investigating executions of their systems during development and diagnosis of software, for performance management. This dissertation proposes the application of machine learning techniques to automatically analyze logs from executions, to challenging tasks in different phases of the software lifecycle. It is shown that the careful application of statistical techniques to features extracted from instrumentation, can distill the rich log data into easily comprehensible forms for the developers

Data Pipeline Quality: Influencing Factors, Root Causes of Data-related Issues, and Processing Problem Areas for Developers

Data pipelines are an integral part of various modern data-driven systems. However, despite their importance, they are often unreliable and deliver poor-quality data. A critical step toward improving this situation is a solid understanding of the aspects contributing to the quality of data pipelines. Therefore, this article first introduces a taxonomy of 41 factors that influence the ability of data pipelines to provide quality data. The taxonomy is based on a multivocal literature review and validated by eight interviews with experts from the data engineering domain. Data, infrastructure, life cycle management, development & deployment, and processing were found to be the main influencing themes. Second, we investigate the root causes of data-related issues, their location in data pipelines, and the main topics of data pipeline processing issues for developers by mining GitHub projects and Stack Overflow posts. We found data-related issues to be primarily caused by incorrect data types (33%), mainly occurring in the data cleaning stage of pipelines (35%). Data integration and ingestion tasks were found to be the most asked topics of developers, accounting for nearly half (47%) of all questions. Compatibility issues were found to be a separate problem area in addition to issues corresponding to the usual data pipeline processing areas (i.e., data loading, ingestion, integration, cleaning, and transformation). These findings suggest that future research efforts should focus on analyzing compatibility and data type issues in more depth and assisting developers in data integration and ingestion tasks. The proposed taxonomy is valuable to practitioners in the context of quality assurance activities and fosters future research into data pipeline quality.Comment: To be published by The Journal of Systems & Softwar