From cluster databases to cloud storage: Providing transactional support on the cloud

Durant les últimes tres dècades, les limitacions tecnològiques (com per exemple la capacitat dels dispositius d'emmagatzematge o l'ample de banda de les xarxes de comunicació) i les creixents demandes dels usuaris (estructures d'informació, volums de dades) han conduït l'evolució de les bases de dades distribuïdes. Des dels primers repositoris de dades per arxius plans que es van desenvolupar en la dècada dels vuitanta, s'han produït importants avenços en els algoritmes de control de concurrència, protocols de replicació i en la gestió de transaccions. No obstant això, els reptes moderns d'emmagatzematge de dades que plantegen el Big Data i el cloud computing—orientats a millorar la limitacions pel que fa a escalabilitat i elasticitat de les bases de dades estàtiques—estan empenyent als professionals a relaxar algunes propietats importants dels sistemes transaccionals clàssics, cosa que exclou a diverses aplicacions les quals no poden encaixar en aquesta estratègia degut a la seva alta dependència transaccional. El propòsit d'aquesta tesi és abordar dos reptes importants encara latents en el camp de les bases de dades distribuïdes: (1) les limitacions pel que fa a escalabilitat dels sistemes transaccionals i (2) el suport transaccional en repositoris d'emmagatzematge en el núvol. Analitzar les tècniques tradicionals de control de concurrència i de replicació, utilitzades per les bases de dades clàssiques per suportar transaccions, és fonamental per identificar les raons que fan que aquests sistemes degradin el seu rendiment quan el nombre de nodes i / o quantitat de dades creix. A més, aquest anàlisi està orientat a justificar el disseny dels repositoris en el núvol que deliberadament han deixat de banda el suport transaccional. Efectivament, apropar el paradigma de l'emmagatzematge en el núvol a les aplicacions que tenen una forta dependència en les transaccions és fonamental per a la seva adaptació als requeriments actuals pel que fa a volums de dades i models de negoci. Aquesta tesi comença amb la proposta d'un simulador de protocols per a bases de dades distribuïdes estàtiques, el qual serveix com a base per a la revisió i comparativa de rendiment dels protocols de control de concurrència i les tècniques de replicació existents. Pel que fa a la escalabilitat de les bases de dades i les transaccions, s'estudien els efectes que té executar diferents perfils de transacció sota diferents condicions. Aquesta anàlisi contínua amb una revisió dels repositoris d'emmagatzematge de dades en el núvol existents—que prometen encaixar en entorns dinàmics que requereixen alta escalabilitat i disponibilitat—, el qual permet avaluar els paràmetres i característiques que aquests sistemes han sacrificat per tal de complir les necessitats actuals pel que fa a emmagatzematge de dades a gran escala. Per explorar les possibilitats que ofereix el paradigma del cloud computing en un escenari real, es presenta el desenvolupament d'una arquitectura d'emmagatzematge de dades inspirada en el cloud computing la qual s’utilitza per emmagatzemar la informació generada en les Smart Grids. Concretament, es combinen les tècniques de replicació en bases de dades transaccionals i la propagació epidèmica amb els principis de disseny usats per construir els repositoris de dades en el núvol. Les lliçons recollides en l'estudi dels protocols de replicació i control de concurrència en el simulador de base de dades, juntament amb les experiències derivades del desenvolupament del repositori de dades per a les Smart Grids, desemboquen en el que hem batejat com Epidemia: una infraestructura d'emmagatzematge per Big Data concebuda per proporcionar suport transaccional en el núvol. A més d'heretar els beneficis dels repositoris en el núvol en quant a escalabilitat, Epidemia inclou una capa de gestió de transaccions que reenvia les transaccions dels clients a un conjunt jeràrquic de particions de dades, cosa que permet al sistema oferir diferents nivells de consistència i adaptar elàsticament la seva configuració a noves demandes de càrrega de treball. Finalment, els resultats experimentals posen de manifest la viabilitat de la nostra contribució i encoratgen als professionals a continuar treballant en aquesta àrea.Durante las últimas tres décadas, las limitaciones tecnológicas (por ejemplo la capacidad de los dispositivos de almacenamiento o el ancho de banda de las redes de comunicación) y las crecientes demandas de los usuarios (estructuras de información, volúmenes de datos) han conducido la evolución de las bases de datos distribuidas. Desde los primeros repositorios de datos para archivos planos que se desarrollaron en la década de los ochenta, se han producido importantes avances en los algoritmos de control de concurrencia, protocolos de replicación y en la gestión de transacciones. Sin embargo, los retos modernos de almacenamiento de datos que plantean el Big Data y el cloud computing—orientados a mejorar la limitaciones en cuanto a escalabilidad y elasticidad de las bases de datos estáticas—están empujando a los profesionales a relajar algunas propiedades importantes de los sistemas transaccionales clásicos, lo que excluye a varias aplicaciones las cuales no pueden encajar en esta estrategia debido a su alta dependencia transaccional. El propósito de esta tesis es abordar dos retos importantes todavía latentes en el campo de las bases de datos distribuidas: (1) las limitaciones en cuanto a escalabilidad de los sistemas transaccionales y (2) el soporte transaccional en repositorios de almacenamiento en la nube. Analizar las técnicas tradicionales de control de concurrencia y de replicación, utilizadas por las bases de datos clásicas para soportar transacciones, es fundamental para identificar las razones que hacen que estos sistemas degraden su rendimiento cuando el número de nodos y/o cantidad de datos crece. Además, este análisis está orientado a justificar el diseño de los repositorios en la nube que deliberadamente han dejado de lado el soporte transaccional. Efectivamente, acercar el paradigma del almacenamiento en la nube a las aplicaciones que tienen una fuerte dependencia en las transacciones es crucial para su adaptación a los requerimientos actuales en cuanto a volúmenes de datos y modelos de negocio. Esta tesis empieza con la propuesta de un simulador de protocolos para bases de datos distribuidas estáticas, el cual sirve como base para la revisión y comparativa de rendimiento de los protocolos de control de concurrencia y las técnicas de replicación existentes. En cuanto a la escalabilidad de las bases de datos y las transacciones, se estudian los efectos que tiene ejecutar distintos perfiles de transacción bajo diferentes condiciones. Este análisis continua con una revisión de los repositorios de almacenamiento en la nube existentes—que prometen encajar en entornos dinámicos que requieren alta escalabilidad y disponibilidad—, el cual permite evaluar los parámetros y características que estos sistemas han sacrificado con el fin de cumplir las necesidades actuales en cuanto a almacenamiento de datos a gran escala. Para explorar las posibilidades que ofrece el paradigma del cloud computing en un escenario real, se presenta el desarrollo de una arquitectura de almacenamiento de datos inspirada en el cloud computing para almacenar la información generada en las Smart Grids. Concretamente, se combinan las técnicas de replicación en bases de datos transaccionales y la propagación epidémica con los principios de diseño usados para construir los repositorios de datos en la nube. Las lecciones recogidas en el estudio de los protocolos de replicación y control de concurrencia en el simulador de base de datos, junto con las experiencias derivadas del desarrollo del repositorio de datos para las Smart Grids, desembocan en lo que hemos acuñado como Epidemia: una infraestructura de almacenamiento para Big Data concebida para proporcionar soporte transaccional en la nube. Además de heredar los beneficios de los repositorios en la nube altamente en cuanto a escalabilidad, Epidemia incluye una capa de gestión de transacciones que reenvía las transacciones de los clientes a un conjunto jerárquico de particiones de datos, lo que permite al sistema ofrecer distintos niveles de consistencia y adaptar elásticamente su configuración a nuevas demandas cargas de trabajo. Por último, los resultados experimentales ponen de manifiesto la viabilidad de nuestra contribución y alientan a los profesionales a continuar trabajando en esta área.Over the past three decades, technology constraints (e.g., capacity of storage devices, communication networks bandwidth) and an ever-increasing set of user demands (e.g., information structures, data volumes) have driven the evolution of distributed databases. Since flat-file data repositories developed in the early eighties, there have been important advances in concurrency control algorithms, replication protocols, and transactions management. However, modern concerns in data storage posed by Big Data and cloud computing—related to overcome the scalability and elasticity limitations of classic databases—are pushing practitioners to relax some important properties featured by transactions, which excludes several applications that are unable to fit in this strategy due to their intrinsic transactional nature. The purpose of this thesis is to address two important challenges still latent in distributed databases: (1) the scalability limitations of transactional databases and (2) providing transactional support on cloud-based storage repositories. Analyzing the traditional concurrency control and replication techniques, used by classic databases to support transactions, is critical to identify the reasons that make these systems degrade their throughput when the number of nodes and/or amount of data rockets. Besides, this analysis is devoted to justify the design rationale behind cloud repositories in which transactions have been generally neglected. Furthermore, enabling applications which are strongly dependent on transactions to take advantage of the cloud storage paradigm is crucial for their adaptation to current data demands and business models. This dissertation starts by proposing a custom protocol simulator for static distributed databases, which serves as a basis for revising and comparing the performance of existing concurrency control protocols and replication techniques. As this thesis is especially concerned with transactions, the effects on the database scalability of different transaction profiles under different conditions are studied. This analysis is followed by a review of existing cloud storage repositories—that claim to be highly dynamic, scalable, and available—, which leads to an evaluation of the parameters and features that these systems have sacrificed in order to meet current large-scale data storage demands. To further explore the possibilities of the cloud computing paradigm in a real-world scenario, a cloud-inspired approach to store data from Smart Grids is presented. More specifically, the proposed architecture combines classic database replication techniques and epidemic updates propagation with the design principles of cloud-based storage. The key insights collected when prototyping the replication and concurrency control protocols at the database simulator, together with the experiences derived from building a large-scale storage repository for Smart Grids, are wrapped up into what we have coined as Epidemia: a storage infrastructure conceived to provide transactional support on the cloud. In addition to inheriting the benefits of highly-scalable cloud repositories, Epidemia includes a transaction management layer that forwards client transactions to a hierarchical set of data partitions, which allows the system to offer different consistency levels and elastically adapt its configuration to incoming workloads. Finally, experimental results highlight the feasibility of our contribution and encourage practitioners to further research in this area

SoK: Understanding BFT Consensus in the Age of Blockchains

Blockchain as an enabler to current Internet infrastructure has provided many unique features and revolutionized current distributed systems into a new era. Its decentralization, immutability, and transparency have attracted many applications to adopt the design philosophy of blockchain and customize various replicated solutions. Under the hood of blockchain, consensus protocols play the most important role to achieve distributed replication systems. The distributed system community has extensively studied the technical components of consensus to reach agreement among a group of nodes. Due to trust issues, it is hard to design a resilient system in practical situations because of the existence of various faults. Byzantine fault-tolerant (BFT) state machine replication (SMR) is regarded as an ideal candidate that can tolerate arbitrary faulty behaviors. However, the inherent complexity of BFT consensus protocols and their rapid evolution makes it hard to practically adapt themselves into application domains. There are many excellent Byzantine-based replicated solutions and ideas that have been contributed to improving performance, availability, or resource efficiency. This paper conducts a systematic and comprehensive study on BFT consensus protocols with a specific focus on the blockchain era. We explore both general principles and practical schemes to achieve consensus under Byzantine settings. We then survey, compare, and categorize the state-of-the-art solutions to understand BFT consensus in detail. For each representative protocol, we conduct an in-depth discussion of its most important architectural building blocks as well as the key techniques they used. We aim that this paper can provide system researchers and developers a concrete view of the current design landscape and help them find solutions to concrete problems. Finally, we present several critical challenges and some potential research directions to advance the research on exploring BFT consensus protocols in the age of blockchains

Enabling and Understanding Failure of Engineering Structures Using the Technique of Cohesive Elements

In this paper, we describe a cohesive zone model for the prediction of failure of engineering solids and/or structures. A damage evolution law is incorporated into a three-dimensional, exponential cohesive law to account for material degradation under the influence of cyclic loading. This cohesive zone model is implemented in the finite element software ABAQUS through a user defined subroutine. The irreversibility of the cohesive zone model is first verified and subsequently applied for studying cyclic crack growth in specimens experiencing different modes of fracture and/or failure. The crack growth behavior to include both crack initiation and crack propagation becomes a natural outcome of the numerical simulation. Numerical examples suggest that the irreversible cohesive zone model can serve as an efficient tool to predict fatigue crack growth. Key issues such as crack path deviation, convergence and mesh dependency are also discussed

A new approach to reversible computing with applications to speculative parallel simulation

In this thesis, we propose an innovative approach to reversible computing that shifts the focus from the operations to the memory outcome of a generic program. This choice allows us to overcome some typical challenges of "plain" reversible computing. Our methodology is to instrument a generic application with the help of an instrumentation tool, namely Hijacker, which we have redesigned and developed for the purpose. Through compile-time instrumentation, we enhance the program's code to keep track of the memory trace it produces until the end. Regardless of the complexity behind the generation of each computational step of the program, we can build inverse machine instructions just by inspecting the instruction that is attempting to write some value to memory. Therefore from this information, we craft an ad-hoc instruction that conveys this old value and the knowledge of where to replace it. This instruction will become part of a more comprehensive structure, namely the reverse window. Through this structure, we have sufficient information to cancel all the updates done by the generic program during its execution. In this writing, we will discuss the structure of the reverse window, as the building block for the whole reversing framework we designed and finally realized. Albeit we settle our solution in the specific context of the parallel discrete event simulation (PDES) adopting the Time Warp synchronization protocol, this framework paves the way for further general-purpose development and employment. We also present two additional innovative contributions coming from our innovative reversibility approach, both of them still embrace traditional state saving-based rollback strategy. The first contribution aims to harness the advantages of both the possible approaches. We implement the rollback operation combining state saving together with our reversible support through a mathematical model. This model enables the system to choose in autonomicity the best rollback strategy, by the mutable runtime dynamics of programs. The second contribution explores an orthogonal direction, still related to reversible computing aspects. In particular, we will address the problem of reversing shared libraries. Indeed, leading from their nature, shared objects are visible to the whole system and so does every possible external modification of their code. As a consequence, it is not possible to instrument them without affecting other unaware applications. We propose a different method to deal with the instrumentation of shared objects. All our innovative proposals have been assessed using the last generation of the open source ROOT-Sim PDES platform, where we integrated our solutions. ROOT-Sim is a C-based package implementing a general purpose simulation environment based on the Time Warp synchronization protocol

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

DTAACS: distributed task allocation for adaptive computational system based on organization knowledge

Doctor of PhilosophyDepartment of Computing and Information SciencesScott A. DeLoachThe Organization-Based Multi-Agent Systems (OMAS) paradigm is an approach to address the challenges posed by complex systems. The complexity of these systems, the changing environment where the systems are deployed, and satisfying higher user expectations are some of current requirements when designing OMAS. For the agents in an OMAS to pursue the achievement of a common goal or task, a certain level of coordination and collaboration occurs among them. An objective in this coordination is to make the decision of who does what. Several solutions have been proposed to answer this task allocation question. The majority of the solutions proposed fall in the categories of marked-based approaches, reactive systems, or game theory approaches. A common fact among these solutions is the system information sharing among agents, which is used only to keep the participant agent informed about other agents activities and mission status. To further exploit and take advantage of this system information shared among agents, a framework is proposed to use this information to answer the question who does what, and reduce the communication among agents. DTAACS-OK is a distributed knowledge-based framework that addresses the Single Agent Task Allocation Problem (SAT-AP) and the Multiple Agent Task Allocation Problem (MAT-AP) in cooperative OMAS. The allocation of tasks is based on an identical organization knowledge posses by all agents in the organization. DTAACS-OK di ers with current solutions in that (a) it is not a marked-based approach where task are auctioned among agents, or (b) it is not based on agents behaviour, where the action or lack of action of an agent cause the reaction of other agents in the organization

Planetary Scale Data Storage

The success of virtualization and container-based application deployment has fundamentally changed computing infrastructure from dedicated hardware provisioning to on-demand, shared clouds of computational resources. One of the most interesting effects of this shift is the opportunity to localize applications in multiple geographies and support mobile users around the globe. With relatively few steps, an application and its data systems can be deployed and scaled across continents and oceans, leveraging the existing data centers of much larger cloud providers. The novelty and ease of a global computing context means that we are closer to the advent of an Oceanstore, an Internet-like revolution in personalized, persistent data that securely travels with its users. At a global scale, however, data systems suffer from physical limitations that significantly impact its consistency and performance. Even with modern telecommunications technology, the latency in communication from Brazil to Japan results in noticeable synchronization delays that violate user expectations. Moreover, the required scale of such systems means that failure is routine. To address these issues, we explore consistency in the implementation of distributed logs, key/value databases and file systems that are replicated across wide areas. At the core of our system is hierarchical consensus, a geographically-distributed consensus algorithm that provides strong consistency, fault tolerance, durability, and adaptability to varying user access patterns. Using hierarchical consensus as a backbone, we further extend our system from data centers to edge regions using federated consistency, an adaptive consistency model that gives satellite replicas high availability at a stronger global consistency than existing weak consistency models. In a deployment of 105 replicas in 15 geographic regions across 5 continents, we show that our implementation provides high throughput, strong consistency, and resiliency in the face of failure. From our experimental validation, we conclude that planetary-scale data storage systems can be implemented algorithmically without sacrificing consistency or performance

Keeping checkpoint/restart viable for exascale systems

Next-generation exascale systems, those capable of performing a quintillion operations per second, are expected to be delivered in the next 8-10 years. These systems, which will be 1,000 times faster than current systems, will be of unprecedented scale. As these systems continue to grow in size, faults will become increasingly common, even over the course of small calculations. Therefore, issues such as fault tolerance and reliability will limit application scalability. Current techniques to ensure progress across faults like checkpoint/restart, the dominant fault tolerance mechanism for the last 25 years, are increasingly problematic at the scales of future systems due to their excessive overheads. In this work, we evaluate a number of techniques to decrease the overhead of checkpoint/restart and keep this method viable for future exascale systems. More specifically, this work evaluates state-machine replication to dramatically increase the checkpoint interval (the time between successive checkpoints) and hash-based, probabilistic incremental checkpointing using graphics processing units to decrease the checkpoint commit time (the time to save one checkpoint). Using a combination of empirical analysis, modeling, and simulation, we study the costs and benefits of these approaches on a wide range of parameters. These results, which cover of number of high-performance computing capability workloads, different failure distributions, hardware mean time to failures, and I/O bandwidths, show the potential benefits of these techniques for meeting the reliability demands of future exascale platforms

Towards Optimal and Practical Asynchronous Byzantine Fault Tolerant Protocols

With recent advancements in blockchain technology, people expect Byzantine fault tolerant (BFT) protocols to be deployed more frequently in wide-area networks (WAN) as opposed to conventional in-house settings. Asynchronous BFT protocols, which do not rely on any form of timing assumption, are arguably robust in such a setting. Asynchronous BFT protocols have been studied since the 1980s, but these asynchronous BFT works mainly focus on understanding the theoretical limits and possibilities. Until the recent asynchronous BFT protocol, HoneyBadgerBFT (HBBFT), was proposed, the field received renewed attention. Dumbo family, a series of our works on the asynchronous BFT protocols, significantly pushed those protocols towards practice. First, all complexity metrics are pushed down to asymptotically optimal, simultaneously. Second, we identify the bottleneck in the state of the art and revisit the design methodology, identifying and utilizing the right components, and optimizing the protocol structure in various ways. Last but not least, we also open the box and optimize the critical components themselves. The resulting protocols are indeed significantly more performant, the latest protocol can have 100K tps and a few seconds of latency at a reasonable scale. This thesis focuses on the latest three members of the Dumbo family. To begin, we solved an open problem by proposing an optimal Multi-valued validated asynchronous Byzantine agreement protocol. Next, we present Dumbo-NG to address the challenge of latency-throughput tension by redesigning the methodology of asynchronous BFT protocols. Another benefit of the new methodology is that it can conquer the censorship threat without extra cost. Furthermore, we consider a realistic environment and present Bolt-Dumbo Transformer (BDT), a generic framework for practical optimistic asynchronous BFT to achieve the "best of both worlds" in terms of the advantages of deterministic BFT and randomized (asynchronous) BFT