7 research outputs found

    On Personal Storage Systems: Architecture and Design Considerations

    Get PDF
    Actualment, els usuaris necessiten grans quantitats d’espai d’emmagatzematge remot per guardar la seva informació personal. En aquesta dissertació, estudiarem dues arquitectures emergents de sistemes d’emmagatzematge d’informació personal: els Núvols Personals (centralitzats) i els sistemes d’emmagatzematge social (descentralitzats). A la Part I d'aquesta tesi, contribuïm desvelant l’operació interna d’un Núvol Personal d’escala global, anomenat UbuntuOne (U1), incloent-hi la seva arquitectura, el seu servei de metadades i les interaccions d’emmagatzematge de dades. A més, proporcionem una anàlisi de la part de servidor d’U1 on estudiem la càrrega del sistema, el comportament dels usuaris i el rendiment del seu servei de metadades. També suggerim tota una sèrie de millores potencials al sistema que poden beneficiar sistemes similars. D'altra banda, en aquesta tesi també contribuïm mesurant i analitzant la qualitat de servei (p.e., velocitat, variabilitat) de les transferències sobre les REST APIs oferides pels Núvols Personals. A més, durant aquest estudi, ens hem adonat que aquestes interfícies poden ser objecte d’abús quan són utilitzades sobre els comptes gratuïts que normalment ofereixen aquests serveis. Això ha motivat l’estudi d’aquesta vulnerabilitat, així com de potencials contramesures. A la Part II d'aquesta dissertació, la nostra primera contribució és analitzar la qualitat de servei que els sistemes d’emmagatzematge social poden proporcionar en termes de disponibilitat de dades, velocitat de transferència i balanceig de la càrrega. El nostre interès principal és entendre com fenòmens intrínsecs, com les dinàmiques de connexió dels usuaris o l’estructura de la xarxa social, limiten el rendiment d’aquests sistemes. També proposem nous mecanismes de manegament de dades per millorar aquestes limitacions. Finalment, dissenyem una arquitectura híbrida que combina recursos del Núvol i dels usuaris. Aquesta arquitectura té com a objectiu millorar la qualitat de servei del sistema i deixa als usuaris decidir la quantitat de recursos utilitzats del Núvol, o en altres paraules, és una decisió entre control de les seves dades i rendiment.Los usuarios cada vez necesitan espacios mayores de almacenamiento en línea para guardar su información personal. Este reto motiva a los investigadores a diseñar y evaluar nuevas infraestructuras de almacenamiento de datos personales. En esta tesis, nos centramos en dos arquitecturas emergentes de almacenamiento de datos personales: las Nubes Personales (centralización) y los sistemas de almacenamiento social (descentralización). Creemos que, pese a su creciente popularidad, estos sistemas requieren de un mayor estudio científico. En la Parte I de esta disertación, examinamos aspectos referentes a la operación interna y el rendimiento de varias Nubes Personales. Concretamente, nuestra primera contribución es desvelar la operación interna e infraestructura de una Nube Personal de gran escala (UbuntuOne, U1). Además, proporcionamos un estudio de la actividad interna de U1 que incluye la carga diaria soportada, el comportamiento de los usuarios y el rendimiento de su sistema de metadatos. También sugerimos mejoras sobre U1 que pueden ser de utilidad en sistemas similares. Por otra parte, en esta tesis medimos y caracterizamos el rendimiento del servicio de REST APIs ofrecido por varias Nubes Personales (velocidad de transferencia, variabilidad, etc.). También demostramos que la combinación de REST APIs sobre cuentas gratuitas de usuario puede dar lugar a abusos por parte de usuarios malintencionados. Esto nos motiva a proponer mecanismos para limitar el impacto de esta vulnerabilidad. En la Parte II de esta tesis, estudiamos la calidad de servicio que pueden ofrecer los sistemas de almacenamiento social en términos de disponibilidad de datos, balanceo de carga y tiempos de transferencia. Nuestro interés principal es entender la manera en que fenómenos intrínsecos, como las dinámicas de conexión de los usuarios o la estructura de su red social, limitan el rendimiento de estos sistemas. También proponemos nuevos mecanismos de gestión de datos para mejorar esas limitaciones. Finalmente, diseñamos y evaluamos una arquitectura híbrida para mejorar la calidad de servicio de los sistemas de almacenamiento social que combina recursos de usuarios y de la Nube. Esta arquitectura permite al usuario decidir su equilibrio entre control de sus datos y rendimiento.Increasingly, end-users demand larger amounts of online storage space to store their personal information. This challenge motivates researchers to devise novel personal storage infrastructures. In this thesis, we focus on two popular personal storage architectures: Personal Clouds (centralized) and social storage systems (decentralized). In our view, despite their growing popularity among users and researchers, there still remain some critical aspects to address regarding these systems. In the Part I of this dissertation, we examine various aspects of the internal operation and performance of various Personal Clouds. Concretely, we first contribute by unveiling the internal structure of a global-scale Personal Cloud, namely UbuntuOne (U1). Moreover, we provide a back-end analysis of U1 that includes the study of the storage workload, the user behavior and the performance of the U1 metadata store. We also suggest improvements to U1 (storage optimizations, user behavior detection and security) that can also benefit similar systems. From an external viewpoint, we actively measure various Personal Clouds through their REST APIs for characterizing their QoS, such as transfer speed, variability and failure rate. We also demonstrate that combining open APIs and free accounts may lead to abuse by malicious parties, which motivates us to propose countermeasures to limit the impact of abusive applications in this scenario. In the Part II of this thesis, we study the storage QoS of social storage systems in terms of data availability, load balancing and transfer times. Our main interest is to understand the way intrinsic phenomena, such as the dynamics of users and the structure of their social relationships, limit the storage QoS of these systems, as well as to research novel mechanisms to ameliorate these limitations. Finally, we design and evaluate a hybrid architecture to enhance the QoS achieved by a social storage system that combines user resources and cloud storage to let users infer the right balance between user control and QoS

    IOStack: Software-Defined Object Storage

    Get PDF
    The complexity and scale of today’s cloud storage systems is growing fast. In response to these challenges, Software- Defined Storage (SDS) has recently become a prime candidate to simplify storage management in the cloud. This article presents IOStack: The first SDS architecture for object stores (OpenStack Swift). At the control plane, the provisioning of SDS services to tenants is made according to a set of policies managed via a high-level DSL. Policies may target storage automation and/or specific SLA objectives. At the data plane, policies define the enforcement of SDS services, namely filters, on a tenant’s requests. Moreover, IOStack is a framework to build a variety of filters, ranging from general-purpose computations close to the data to specialized data management mechanisms. Our experiments illustrate that IOStack enables easy and effective policy-based provisioning, which can significantly improve the operation of a multi-tenant object store.This work has been funded by the European Union through project H2020 “IOStack: Software-Defined Storage for Big Data” (644182) and by the Spanish Ministry of Science and Innovation through project “Servicios Cloud y Redes Comunitarias” (TIN-2013-47245-C2-2-R).Peer ReviewedPostprint (author's final draft

    Dissecting UbuntuOne: Autopsy of a Global-scale Personal Cloud Back-end

    Get PDF
    Personal Cloud services, such as Dropbox or Box, have been widely adopted by users. Unfortunately, very little is known about the internal operation and general characteristics of Personal Clouds since they are proprietary services. In this paper, we focus on understanding the nature of Personal Clouds by presenting the internal structure and a measurement study of UbuntuOne (U1). We first detail the U11 architecture, core components involved in the U1 metadata service hosted in the datacenter of Canonical, as well as the interactions of U11 with Amazon S3 to outsource data storage. To our knowledge, this is the first research work to describe the internals of a large-scale Personal Cloud. Second, by means of tracing the U11 servers, we provide an extensive analysis of its back-end activity for one month. Our analysis includes the study of the storage workload, the user behavior and the performance of the U1 metadata store. Moreover, based on our analysis, we suggest improvements to U1 that can also benefit similar Personal Cloud systems. Finally, we contribute our dataset to the community, which is the first to contain the back-end activity of a large-scale Personal Cloud. We believe that our dataset provides unique opportunities for extending research in the field

    A survey and classification of software-defined storage systems

    Get PDF
    The exponential growth of digital information is imposing increasing scale and efficiency demands on modern storage infrastructures. As infrastructure complexity increases, so does the difficulty in ensuring quality of service, maintainability, and resource fairness, raising unprecedented performance, scalability, and programmability challenges. Software-Defined Storage (SDS) addresses these challenges by cleanly disentangling control and data flows, easing management, and improving control functionality of conventional storage systems. Despite its momentum in the research community, many aspects of the paradigm are still unclear, undefined, and unexplored, leading to misunderstandings that hamper the research and development of novel SDS technologies. In this article, we present an in-depth study of SDS systems, providing a thorough description and categorization of each plane of functionality. Further, we propose a taxonomy and classification of existing SDS solutions according to different criteria. Finally, we provide key insights about the paradigm and discuss potential future research directions for the field.This work was financed by the Portuguese funding agency FCT-Fundacao para a Ciencia e a Tecnologia through national funds, the PhD grant SFRH/BD/146059/2019, the project ThreatAdapt (FCT-FNR/0002/2018), the LASIGE Research Unit (UIDB/00408/2020), and cofunded by the FEDER, where applicable

    Giving wings to your data: A first experience of Personal Cloud interoperability

    No full text
    Article pendent de publicaciĂł DOI: 10.1016/j.future.2017.01.027 FiliaciĂł URV: SIPersonal Clouds are becoming increasingly popular storage services for end-users and organizations. However, the competition among Personal Clouds, their proprietary nature and the heterogeneity of synchronization protocols have led to a complete lack of interoperability among them. Regrettably, this situation impedes that users share data transparently across multiple providers. Even worse, the lack of interoperability has associated serious risks, such as vendor lock-in, in which users get trapped in a single provider due to the cost of switching to another one. In this work, we contribute DataWings: The first interoperability protocol for Personal Clouds. DataWings consists of an authentication management protocol and a storage API for file storage, synchronization and sharing that adhere to the current authentication (OAuth) and REST standards, respectively. Moreover, we demonstrate the feasibility of DataWings by implementing the protocol in various providers (NEC, StackSync, eyeOS) and performing a real deployment evaluated with real trace replays of production systems (UbuntuOne, NEC). To our knowledge, this is the first real-world experience of Personal Cloud interoperability. Our experiments provide new insights on the performance implications that different types of user activity and the underlying sharing network topology have on the implementation of our protocol. We conclude that DataWings is flexible enough to leverage interoperability for heterogeneous Personal Clouds, opening the door for a broader adoption by other vendors

    IOStack: Software-Defined Object Storage

    No full text
    The complexity and scale of today’s cloud storage systems is growing fast. In response to these challenges, Software- Defined Storage (SDS) has recently become a prime candidate to simplify storage management in the cloud. This article presents IOStack: The first SDS architecture for object stores (OpenStack Swift). At the control plane, the provisioning of SDS services to tenants is made according to a set of policies managed via a high-level DSL. Policies may target storage automation and/or specific SLA objectives. At the data plane, policies define the enforcement of SDS services, namely filters, on a tenant’s requests. Moreover, IOStack is a framework to build a variety of filters, ranging from general-purpose computations close to the data to specialized data management mechanisms. Our experiments illustrate that IOStack enables easy and effective policy-based provisioning, which can significantly improve the operation of a multi-tenant object store.This work has been funded by the European Union through project H2020 “IOStack: Software-Defined Storage for Big Data” (644182) and by the Spanish Ministry of Science and Innovation through project “Servicios Cloud y Redes Comunitarias” (TIN-2013-47245-C2-2-R).Peer Reviewe
    corecore