4,144 research outputs found
Serverless Strategies and Tools in the Cloud Computing Continuum
Tesis por compendio[ES] En los últimos años, la popularidad de la computación en nube ha permitido a los usuarios acceder a recursos de cómputo, red y almacenamiento sin precedentes bajo un modelo de pago por uso. Esta popularidad ha propiciado la aparición de nuevos servicios para resolver determinados problemas informáticos a gran escala y simplificar el desarrollo y el despliegue de aplicaciones. Entre los servicios más destacados en los últimos años se encuentran las plataformas FaaS (Función como Servicio), cuyo principal atractivo es la facilidad de despliegue de pequeños fragmentos de código en determinados lenguajes de programación para realizar tareas específicas en respuesta a eventos. Estas funciones son ejecutadas en los servidores del proveedor Cloud sin que los usuarios se preocupen de su mantenimiento ni de la gestión de su elasticidad, manteniendo siempre un modelo de pago por uso de grano fino.
Las plataformas FaaS pertenecen al paradigma informático conocido como Serverless, cuyo propósito es abstraer la gestión de servidores por parte de los usuarios, permitiéndoles centrar sus esfuerzos únicamente en el desarrollo de aplicaciones. El problema del modelo FaaS es que está enfocado principalmente en microservicios y tiende a tener limitaciones en el tiempo de ejecución y en las capacidades de computación (por ejemplo, carece de soporte para hardware de aceleración como GPUs). Sin embargo, se ha demostrado que la capacidad de autoaprovisionamiento y el alto grado de paralelismo de estos servicios pueden ser muy adecuados para una mayor variedad de aplicaciones. Además, su inherente ejecución dirigida por eventos hace que las funciones sean perfectamente adecuadas para ser definidas como pasos en flujos de trabajo de procesamiento de archivos (por ejemplo, flujos de trabajo de computación científica).
Por otra parte, el auge de los dispositivos inteligentes e integrados (IoT), las innovaciones en las redes de comunicación y la necesidad de reducir la latencia en casos de uso complejos han dado lugar al concepto de Edge computing, o computación en el borde. El Edge computing consiste en el procesamiento en dispositivos cercanos a las fuentes de datos para mejorar los tiempos de respuesta. La combinación de este paradigma con la computación en nube, formando arquitecturas con dispositivos a distintos niveles en función de su proximidad a la fuente y su capacidad de cómputo, se ha acuñado como continuo de la computación en la nube (o continuo computacional).
Esta tesis doctoral pretende, por lo tanto, aplicar diferentes estrategias Serverless para permitir el despliegue de aplicaciones generalistas, empaquetadas en contenedores de software, a través de los diferentes niveles del continuo computacional. Para ello, se han desarrollado múltiples herramientas con el fin de: i) adaptar servicios FaaS de proveedores Cloud públicos; ii) integrar diferentes componentes software para definir una plataforma Serverless en infraestructuras privadas y en el borde; iii) aprovechar dispositivos de aceleración en plataformas Serverless; y iv) facilitar el despliegue de aplicaciones y flujos de trabajo a través de interfaces de usuario. Además, se han creado y adaptado varios casos de uso para evaluar los desarrollos conseguidos.[CA] En els últims anys, la popularitat de la computació al núvol ha permès als usuaris accedir a recursos de còmput, xarxa i emmagatzematge sense precedents sota un model de pagament per ús. Aquesta popularitat ha propiciat l'aparició de nous serveis per resoldre determinats problemes informàtics a gran escala i simplificar el desenvolupament i desplegament d'aplicacions. Entre els serveis més destacats en els darrers anys hi ha les plataformes FaaS (Funcions com a Servei), el principal atractiu de les quals és la facilitat de desplegament de petits fragments de codi en determinats llenguatges de programació per realitzar tasques específiques en resposta a esdeveniments. Aquestes funcions són executades als servidors del proveïdor Cloud sense que els usuaris es preocupen del seu manteniment ni de la gestió de la seva elasticitat, mantenint sempre un model de pagament per ús de gra fi.
Les plataformes FaaS pertanyen al paradigma informàtic conegut com a Serverless, el propòsit del qual és abstraure la gestió de servidors per part dels usuaris, permetent centrar els seus esforços únicament en el desenvolupament d'aplicacions. El problema del model FaaS és que està enfocat principalment a microserveis i tendeix a tenir limitacions en el temps d'execució i en les capacitats de computació (per exemple, no té suport per a maquinari d'acceleració com GPU). Tot i això, s'ha demostrat que la capacitat d'autoaprovisionament i l'alt grau de paral·lelisme d'aquests serveis poden ser molt adequats per a més aplicacions. A més, la seva inherent execució dirigida per esdeveniments fa que les funcions siguen perfectament adequades per ser definides com a passos en fluxos de treball de processament d'arxius (per exemple, fluxos de treball de computació científica).
D'altra banda, l'auge dels dispositius intel·ligents i integrats (IoT), les innovacions a les xarxes de comunicació i la necessitat de reduir la latència en casos d'ús complexos han donat lloc al concepte d'Edge computing, o computació a la vora. L'Edge computing consisteix en el processament en dispositius propers a les fonts de dades per millorar els temps de resposta. La combinació d'aquest paradigma amb la computació en núvol, formant arquitectures amb dispositius a diferents nivells en funció de la proximitat a la font i la capacitat de còmput, s'ha encunyat com a continu de la computació al núvol (o continu computacional).
Aquesta tesi doctoral pretén, doncs, aplicar diferents estratègies Serverless per permetre el desplegament d'aplicacions generalistes, empaquetades en contenidors de programari, a través dels diferents nivells del continu computacional. Per això, s'han desenvolupat múltiples eines per tal de: i) adaptar serveis FaaS de proveïdors Cloud públics; ii) integrar diferents components de programari per definir una plataforma Serverless en infraestructures privades i a la vora; iii) aprofitar dispositius d'acceleració a plataformes Serverless; i iv) facilitar el desplegament d'aplicacions i fluxos de treball mitjançant interfícies d'usuari. A més, s'han creat i s'han adaptat diversos casos d'ús per avaluar els desenvolupaments aconseguits.[EN] In recent years, the popularity of Cloud computing has allowed users to access unprecedented compute, network, and storage resources under a pay-per-use model. This popularity led to new services to solve specific large-scale computing challenges and simplify the development and deployment of applications. Among the most prominent services in recent years are FaaS (Function as a Service) platforms, whose primary appeal is the ease of deploying small pieces of code in certain programming languages to perform specific tasks on an event-driven basis. These functions are executed on the Cloud provider's servers without users worrying about their maintenance or elasticity management, always keeping a fine-grained pay-per-use model.
FaaS platforms belong to the computing paradigm known as Serverless, which aims to abstract the management of servers from the users, allowing them to focus their efforts solely on the development of applications. The problem with FaaS is that it focuses on microservices and tends to have limitations regarding the execution time and the computing capabilities (e.g. lack of support for acceleration hardware such as GPUs). However, it has been demonstrated that the self-provisioning capability and high degree of parallelism of these services can be well suited to broader applications. In addition, their inherent event-driven triggering makes functions perfectly suitable to be defined as steps in file processing workflows (e.g. scientific computing workflows).
Furthermore, the rise of smart and embedded devices (IoT), innovations in communication networks and the need to reduce latency in challenging use cases have led to the concept of Edge computing. Edge computing consists of conducting the processing on devices close to the data sources to improve response times. The coupling of this paradigm together with Cloud computing, involving architectures with devices at different levels depending on their proximity to the source and their compute capability, has been coined as Cloud Computing Continuum (or Computing Continuum).
Therefore, this PhD thesis aims to apply different Serverless strategies to enable the deployment of generalist applications, packaged in software containers, across the different tiers of the Cloud Computing Continuum. To this end, multiple tools have been developed in order to: i) adapt FaaS services from public Cloud providers; ii) integrate different software components to define a Serverless platform on on-premises and Edge infrastructures; iii) leverage acceleration devices on Serverless platforms; and iv) facilitate the deployment of applications and workflows through user interfaces. Additionally, several use cases have been created and adapted to assess the developments achieved.Risco Gallardo, S. (2023). Serverless Strategies and Tools in the Cloud Computing Continuum [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/202013Compendi
A Trust Management Framework for Vehicular Ad Hoc Networks
The inception of Vehicular Ad Hoc Networks (VANETs) provides an opportunity for road users and public infrastructure to share information that improves the operation of roads and the driver experience. However, such systems can be vulnerable to malicious external entities and legitimate users. Trust management is used to address attacks from legitimate users in accordance with a user’s trust score. Trust models evaluate messages to assign rewards or punishments. This can be used to influence a driver’s future behaviour or, in extremis, block the driver. With receiver-side schemes, various methods are used to evaluate trust including, reputation computation, neighbour recommendations, and storing historical information. However, they incur overhead and add a delay when deciding whether to accept or reject messages. In this thesis, we propose a novel Tamper-Proof Device (TPD) based trust framework for managing trust of multiple drivers at the sender side vehicle that updates trust, stores, and protects information from malicious tampering. The TPD also regulates, rewards, and punishes each specific driver, as required. Furthermore, the trust score determines the classes of message that a driver can access. Dissemination of feedback is only required when there is an attack (conflicting information). A Road-Side Unit (RSU) rules on a dispute, using either the sum of products of trust and feedback or official vehicle data if available. These “untrue attacks” are resolved by an RSU using collaboration, and then providing a fixed amount of reward and punishment, as appropriate. Repeated attacks are addressed by incremental punishments and potentially driver access-blocking when conditions are met. The lack of sophistication in this fixed RSU assessment scheme is then addressed by a novel fuzzy logic-based RSU approach. This determines a fairer level of reward and punishment based on the severity of incident, driver past behaviour, and RSU confidence. The fuzzy RSU controller assesses judgements in such a way as to encourage drivers to improve their behaviour. Although any driver can lie in any situation, we believe that trustworthy drivers are more likely to remain so, and vice versa. We capture this behaviour in a Markov chain model for the sender and reporter driver behaviours where a driver’s truthfulness is influenced by their trust score and trust state. For each trust state, the driver’s likelihood of lying or honesty is set by a probability distribution which is different for each state. This framework is analysed in Veins using various classes of vehicles under different traffic conditions. Results confirm that the framework operates effectively in the presence of untrue and inconsistent attacks. The correct functioning is confirmed with the system appropriately classifying incidents when clarifier vehicles send truthful feedback. The framework is also evaluated against a centralized reputation scheme and the results demonstrate that it outperforms the reputation approach in terms of reduced communication overhead and shorter response time. Next, we perform a set of experiments to evaluate the performance of the fuzzy assessment in Veins. The fuzzy and fixed RSU assessment schemes are compared, and the results show that the fuzzy scheme provides better overall driver behaviour. The Markov chain driver behaviour model is also examined when changing the initial trust score of all drivers
UMSL Bulletin 2022-2023
The 2022-2023 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1087/thumbnail.jp
Mapping the Focal Points of WordPress: A Software and Critical Code Analysis
Programming languages or code can be examined through numerous analytical lenses. This project is a critical analysis of WordPress, a prevalent web content management system, applying four modes of inquiry. The project draws on theoretical perspectives and areas of study in media, software, platforms, code, language, and power structures. The applied research is based on Critical Code Studies, an interdisciplinary field of study that holds the potential as a theoretical lens and methodological toolkit to understand computational code beyond its function. The project begins with a critical code analysis of WordPress, examining its origins and source code and mapping selected vulnerabilities. An examination of the influence of digital and computational thinking follows this. The work also explores the intersection of code patching and vulnerability management and how code shapes our sense of control, trust, and empathy, ultimately arguing that a rhetorical-cultural lens can be used to better understand code\u27s controlling influence. Recurring themes throughout these analyses and observations are the connections to power and vulnerability in WordPress\u27 code and how cultural, processual, rhetorical, and ethical implications can be expressed through its code, creating a particular worldview. Code\u27s emergent properties help illustrate how human values and practices (e.g., empathy, aesthetics, language, and trust) become encoded in software design and how people perceive the software through its worldview. These connected analyses reveal cultural, processual, and vulnerability focal points and the influence these entanglements have concerning WordPress as code, software, and platform. WordPress is a complex sociotechnical platform worthy of further study, as is the interdisciplinary merging of theoretical perspectives and disciplines to critically examine code. Ultimately, this project helps further enrich the field by introducing focal points in code, examining sociocultural phenomena within the code, and offering techniques to apply critical code methods
ACiS: smart switches with application-level acceleration
Network performance has contributed fundamentally to the growth of supercomputing over the past decades. In parallel, High Performance Computing (HPC) peak performance has depended, first, on ever faster/denser CPUs, and then, just on increasing density alone. As operating frequency, and now feature size, have levelled off, two new approaches are becoming central to achieving higher net performance: configurability and integration. Configurability enables hardware to map to the application, as well as vice versa. Integration enables system components that have generally been single function-e.g., a network to transport data—to have additional functionality, e.g., also to operate on that data. More generally, integration enables compute-everywhere: not just in CPU and accelerator, but also in network and, more specifically, the communication switches.
In this thesis, we propose four novel methods of enhancing HPC performance through Advanced Computing in the Switch (ACiS). More specifically, we propose various flexible and application-aware accelerators that can be embedded into or attached to existing communication switches to improve the performance and scalability of HPC and Machine Learning (ML) applications. We follow a modular design discipline through introducing composable plugins to successively add ACiS capabilities.
In the first work, we propose an inline accelerator to communication switches for user-definable collective operations. MPI collective operations can often be performance killers in HPC applications; we seek to solve this bottleneck by offloading them to reconfigurable hardware within the switch itself. We also introduce a novel mechanism that enables the hardware to support MPI communicators of arbitrary shape and that is scalable to very large systems.
In the second work, we propose a look-aside accelerator for communication switches that is capable of processing packets at line-rate. Functions requiring loops and states are addressed in this method. The proposed in-switch accelerator is based on a RISC-V compatible Coarse Grained Reconfigurable Arrays (CGRAs).
To facilitate usability, we have developed a framework to compile user-provided C/C++ codes to appropriate back-end instructions for configuring the accelerator.
In the third work, we extend ACiS to support fused collectives and the combining of collectives with map operations. We observe that there is an opportunity of fusing communication (collectives) with computation. Since the computation can vary for different applications, ACiS support should be programmable in this method.
In the fourth work, we propose that switches with ACiS support can control and manage the execution of applications, i.e., that the switch be an active device with decision-making capabilities. Switches have a central view of the network; they can collect telemetry information and monitor application behavior and then use this information for control, decision-making, and coordination of nodes.
We evaluate the feasibility of ACiS through extensive RTL-based simulation as well as deployment in an open-access cloud infrastructure. Using this simulation framework, when considering a Graph Convolutional Network (GCN) application as a case study, a speedup of on average 3.4x across five real-world datasets is achieved on 24 nodes compared to a CPU cluster without ACiS capabilities
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