Why logical clocks are easy

Tracking causality should not be ignored. It is important in the design of many distributed algorithms. And not respecting causality can lead to strange behaviors for users. The most commonly used mechanisms for tracking causality, vector clocks and version vectors, are simply optimized representations of causal histories, which are easy to understand. By building on the notion of causal histories, users can begin to see the logic ehind these mechanisms, to identify how they differ, and even consider possible optimizations. When confronted with an unfamiliar causality tracking mechanism, or when trying to design a new system that requires it, readers should ask two simple questions, which events need tracking and how does the mechanism translate back to a simple causal history.We would like to thank Rodrigo Rodrigues, Marc Shapiro, Russell Brown, Sean Cribbs, and Justin Sheehy for their feedback. This work was partially supported by EU FP7 SyncFree project (609551) and FCT/MCT projects UID/CEC/04516/2013 and UID/EEA/50014/2013.info:eu-repo/semantics/publishedVersio

Time, Simultaneity, and Causality in Wireless Networks with Sensing and Communications

Wireless systems beyond 5G evolve towards embracing both sensing and communication, resulting in increased convergence of the digital and the physical world. The existence of fused digital-physical realms raises critical questions regarding temporal ordering, causality, and the synchronization of events. This paper addresses the temporal challenges arising from the fact that the wireless infrastructure becomes an entity with multisensory perception. With the growing reliance on real-time interactions and applications such as digital twins, extended reality, and the metaverse, the need for accurate timestamping and temporal forensics becomes crucial. The paper introduces a model that incorporates Temporal Windows of Integration (TWI) to emulate human multisensory perception and discusses the implications for setting timing constraints in real-time applications and enabling temporal forensics. The analysis explores trade-offs, probabilities, and bounds for simultaneity and causality violation in the context of wireless systems evolving towards perceptive networks. This work underscores the significance of timestamping in the evolving wireless landscape, provide insights into system-level implications, and points out new research avenues for systems that combine sensing and communications.Comment: Submitted for possible publicatio

Una implementación rápida de Parallel Snapshot Isolation

Grado en Ingeniería Informática, Facultad de Informática UCM, Departamento de Arquitectura de Computadores y Automática, Curso 2019/2020.Most distributed database systems offer weak consistency models in order to avoid the performance penalty of coordinating replicas. Ideally, distributed databases would offer strong consistency models, like serialisability, since they make it easy to verify application invariants, and free programmers from worrying about concurrency. However, implementing and scaling systems with strong consistency is difficult, since it usually requires global communication. Weak models, while easier to scale, impose on the programmers the need to reason about possible anomalies, and the need to implement conflict resolution mechanisms in application code. Recently proposed consistency models, like Parallel Snapshot Isolation (PSI) and NonMonotonic Snapshot Isolation (NMSI), represent the strongest models that still allow to build scalable systems without global communication. They allow comparable performance to previous, weaker models, as well as similar abort rates. However, both models still provide weaker guarantees than serialisability, and may prove difficult to use in applications. This work shows an approach to bridge the gap between PSI, NMSI and strong consistency models like serialisability. It introduces and implements fastPSI, a consistency protocol that allows the user to selectively enforce serialisability for certain executions, while retaining the scalability properties of weaker consistency models like PSI and NMSI. In addition, it features a comprehensive evaluation of fastPSI in comparison with other consistency protocols, both weak and strong, showing that fastPSI offers better performance than serialisability, while retaining the scalability of weaker protocols.La mayoría de las bases de datos distribuidas ofrecen modelos de consistencia débil, con la finalidad de evitar la penalización de rendimiento que supone la coordinación de las distintas réplicas. Idealmente, las bases de datos distribuidas ofrecerían modelos de consistencia fuerte, como serialisability, ya que facilitan la verificación de los invariantes de las aplicaciones, y permiten que los programadores no deban preocuparse sobre posibles problemas de concurrencia. Sin embargo, implementar sistemas escalables que con modelos de consistencia fuerte no es fácil, pues requieren el uso de comunicación global. Sin embargo, aunque los modelos de consistencia más débiles permiten sistemas más escalables, imponen en los programadores la necesidad de razonar sobre posibles anomalías, así como implementar mecanismos de resolución de conflictos en el código de las aplicaciones. Dos modelos de consistencia propuestos recientemente, Parallel Snapshot Isolation (PSI) y Non-Monotonic Snapshot Isolation (NMSI), representan los modelos más fuertes que permiten implementaciones escalables sin necesidad de comunicación global. Permiten, a su vez, implementar sistemas con rendimientos similares a aquellos con modelos más débiles, a la vez que mantienen tasas de cancelación de transacciones similares. Aun así, ambos modelos no logran ofrecer las mismas garantías que serialisability, por lo que pueden ser difíciles de usar desde el punto de vista de las aplicaciones. Este trabajo presenta una propuesta que busca acortar la distancia entre modelos como PSI y NMSI y modelos fuertes como serialisability. Con esa finalidad, este trabajo presenta fastPSI, un protocolo de consistencia que permite al usuario ejecutar de manera selectiva transacciones serializables, reteniendo a su vez las propiedades de escalabilidad propias de modelos de consistencia débiles como PSI o NMSI. Además, este trabajo cuenta con una evaluación exhaustiva de fastPSI, comparándolo con otros protocolos de consistencia, tanto fuertes como débiles. Se muestra así que fastPSI logra un rendimiento mayor que serialisability sin por ello renunciar a la escalabilidad de protocolos más débiles.Depto. de Arquitectura de Computadores y AutomáticaFac. de InformáticaTRUEunpu

A Semantic Consistency Model to Reduce Coordination in Replicated Systems

Large-scale distributed applications need to be available and responsive to satisfy millions of users, which can be achieved by having data geo-replicated in multiple replicas. However, a partitioned system cannot sustain availability and consistency at fully. The usage of weak consistency models might lead to data integrity violations, triggered by problematic concurrent updates, such as selling twice the last ticket on a flight company service. To overcome possible conflicts, programmers might opt to apply strong consistency, which guarantees a total order between operations, while preserving data integrity. Nevertheless, the illusion of being a non-replicated system affects its availability. In contrast, weaker notions might be used, such as eventual consistency, that boosts responsiveness, as operations are executed directly at the source replica and their effects are propagated to remote replicas in the background. However, this approach might put data integrity at risk. Current protocols that preserve invariants rely on, at least, causal consistency, a consistency model that maintains causal dependencies between operations. In this dissertation, we propose a protocol that includes a semantic consistency model. This consistency model stands between eventual consistency and causal consistency. We guarantee better performance comparing with causal consistency, and ensure data integrity. Through semantic analysis, relying on the static analysis tool CISE3, we manage to limit the maximum number of dependencies that each operation will have. To support the protocol, we developed a communication algorithm in a cluster. Additionally, we present an architecture that uses Akka, an actor-based middleware in which actors communicate by exchanging messages. This architecture adopts the publish/subscribe pattern and includes data persistence. We also consider the stability of operations, as well as a dynamic cluster environment, ensuring the convergence of the replicated state. Finally, we perform an experimental evaluation regarding the performance of the algorithm using standard case studies. The evaluation confirms that by relying on semantic analysis, the system requires less coordination between the replicas than causal consistency, ensuring data integrity.Aplicações distribuídas em larga escala necessitam de estar disponíveis e de serem responsivas para satisfazer milhões de utilizadores, o que pode ser alcançado através da geo-replicação dos dados em múltiplas réplicas. No entanto, um sistema particionado não consegue garantir disponibilidade e consistência na sua totalidade. O uso de modelos de consistência fraca pode levar a violações da integridade dos dados, originadas por escritas concorrentes problemáticas. Para superar possíveis conflitos, os programadores podem optar por aplicar modelos de consistência forte, originando uma ordem total das operações, assegurando a integridade dos dados. Em contrapartida, podem ser utilizadas noções mais fracas, como a consistência eventual, que aumenta a capacidade de resposta, uma vez que as operações são executadas diretamente na réplica de origem e os seus efeitos são propagados para réplicas remotas. No entanto, esta abordagem pode colocar em risco a integridade dos dados. Os protocolos existentes que preservam as invariantes dependem, pelo menos, da consistência causal, um modelo de consistência que mantém as dependências causais entre operações. Nesta dissertação propomos um protocolo que inclui um modelo de consistência semântica. Este modelo situa-se entre a consistência eventual e a consistência causal. Garantimos um melhor desempenho em comparação com a consistência causal, e asseguramos a integridade dos dados. Através de uma análise semântica, obtida através da ferramenta de análise estática CISE3, conseguimos limitar o número de dependências de cada operação. Para suportar o protocolo, desenvolvemos um algoritmo de comunicação entre um aglomerado de réplicas. Adicionalmente, apresentamos uma arquitetura que utiliza Akka, um middleware baseado em atores que trocam mensagens entre si. Esta arquitetura utiliza o padrão publish/subscribe e inclui a persistência dos dados. Consideramos também a estabilidade das operações, bem como um ambiente dinâmico de réplicas, assegurando a convergência do estado. Por último, apresentamos a avaliação do desempenho do algoritmo desenvolvido, que confirma que a análise semântica das operações requer menos coordenação entre as réplicas que a consistência causal

A novel causally consistent replication protocol with partial geo-replication

Distributed storage systems are a fundamental component of large-scale Internet services. To keep up with the increasing expectations of users regarding availability and latency, the design of data storage systems has evolved to achieve these properties, by exploiting techniques such as partial replication, geo-replication and weaker consistency models. While systems with these characteristics exist, they usually do not provide all these properties or do so in an inefficient manner, not taking full advantage of them. Additionally, weak consistency models, such as eventual consistency, put an excessively high burden on application programmers for writing correct applications, and hence, multiple systems have moved towards providing additional consistency guarantees such as implementing the causal (and causal+) consistency models. In this thesis we approach the existing challenges in designing a causally consistent replication protocol, with a focus on the use of geo and partial data replication. To this end, we present a novel replication protocol, capable of enriching an existing geo and partially replicated datastore with the causal+ consistency model. In addition, this thesis also presents a concrete implementation of the proposed protocol over the popular Cassandra datastore system. This implementation is complemented with experimental results obtained in a realistic scenario, in which we compare our proposal withmultiple configurations of the Cassandra datastore (without causal consistency guarantees) and with other existing alternatives. The results show that our proposed solution is able to achieve a balanced performance, with low data visibility delays and without significant performance penalties

OSCAR. A Noise Injection Framework for Testing Concurrent Software

“Moore’s Law” is a well-known observable phenomenon in computer science that describes a visible yearly pattern in processor’s die increase. Even though it has held true for the last 57 years, thermal limitations on how much a processor’s core frequencies can be increased, have led to physical limitations to their performance scaling. The industry has since then shifted towards multicore architectures, which offer much better and scalable performance, while in turn forcing programmers to adopt the concurrent programming paradigm when designing new software, if they wish to make use of this added performance. The use of this paradigm comes with the unfortunate downside of the sudden appearance of a plethora of additional errors in their programs, stemming directly from their (poor) use of concurrency techniques. Furthermore, these concurrent programs themselves are notoriously hard to design and to verify their correctness, with researchers continuously developing new, more effective and effi- cient methods of doing so. Noise injection, the theme of this dissertation, is one such method. It relies on the “probe effect” — the observable shift in the behaviour of concurrent programs upon the introduction of noise into their routines. The abandonment of ConTest, a popular proprietary and closed-source noise injection framework, for testing concurrent software written using the Java programming language, has left a void in the availability of noise injection frameworks for this programming language. To mitigate this void, this dissertation proposes OSCAR — a novel open-source noise injection framework for the Java programming language, relying on static bytecode instrumentation for injecting noise. OSCAR will provide a free and well-documented noise injection tool for research, pedagogical and industry usage. Additionally, we propose a novel taxonomy for categorizing new and existing noise injection heuristics, together with a new method for generating and analysing concurrent software traces, based on string comparison metrics. After noising programs from the IBM Concurrent Benchmark with different heuristics, we observed that OSCAR is highly effective in increasing the coverage of the interleaving space, and that the different heuristics provide diverse trade-offs on the cost and benefit (time/coverage) of the noise injection process.Resumo A “Lei de Moore” é um fenómeno, bem conhecido na área das ciências da computação, que descreve um padrão evidente no aumento anual da densidade de transístores num processador. Mesmo mantendo-se válido nos últimos 57 anos, o aumento do desempenho dos processadores continua garrotado pelas limitações térmicas inerentes `a subida da sua frequência de funciona- mento. Desde então, a industria transitou para arquiteturas multi núcleo, com significativamente melhor e mais escalável desempenho, mas obrigando os programadores a adotar o paradigma de programação concorrente ao desenhar os seus novos programas, para poderem aproveitar o desempenho adicional que advém do seu uso. O uso deste paradigma, no entanto, traz consigo, por consequência, a introdução de uma panóplia de novos erros nos programas, decorrentes diretamente da utilização (inadequada) de técnicas de programação concorrente. Adicionalmente, estes programas concorrentes são conhecidos por serem consideravelmente mais difíceis de desenhar e de validar, quanto ao seu correto funcionamento, incentivando investi- gadores ao desenvolvimento de novos métodos mais eficientes e eficazes de o fazerem. A injeção de ruído, o tema principal desta dissertação, é um destes métodos. Esta baseia-se no “efeito sonda” (do inglês “probe effect”) — caracterizado por uma mudança de comportamento observável em programas concorrentes, ao terem ruído introduzido nas suas rotinas. Com o abandono do Con- Test, uma framework popular, proprietária e de código fechado, de análise dinâmica de programas concorrentes através de injecção de ruído, escritos com recurso `a linguagem de programação Java, viu-se surgir um vazio na oferta de framework de injeção de ruído, para esta mesma linguagem. Para mitigar este vazio, esta dissertação propõe o OSCAR — uma nova framework de injeção de ruído, de código-aberto, para a linguagem de programação Java, que utiliza manipulação estática de bytecode para realizar a introdução de ruído. O OSCAR pretende oferecer uma ferramenta livre e bem documentada de injeção de ruído para fins de investigação, pedagógicos ou até para a indústria. Adicionalmente, a dissertação propõe uma nova taxonomia para categorizar os dife- rentes tipos de heurísticas de injecção de ruídos novos e existentes, juntamente com um método para gerar e analisar traces de programas concorrentes, com base em métricas de comparação de strings. Após inserir ruído em programas do IBM Concurrent Benchmark, com diversas heurísticas, ob- servámos que o OSCAR consegue aumentar significativamente a dimensão da cobertura do espaço de estados de programas concorrentes. Adicionalmente, verificou-se que diferentes heurísticas produzem um leque variado de prós e contras, especialmente em termos de eficácia versus eficiência