uFLIP: Understanding Flash IO Patterns

Does the advent of flash devices constitute a radical change for secondary storage? How should database systems adapt to this new form of secondary storage? Before we can answer these questions, we need to fully understand the performance characteristics of flash devices. More specifically, we want to establish what kind of IOs should be favored (or avoided) when designing algorithms and architectures for flash-based systems. In this paper, we focus on flash IO patterns, that capture relevant distribution of IOs in time and space, and our goal is to quantify their performance. We define uFLIP, a benchmark for measuring the response time of flash IO patterns. We also present a benchmarking methodology which takes into account the particular characteristics of flash devices. Finally, we present the results obtained by measuring eleven flash devices, and derive a set of design hints that should drive the development of flash-based systems on current devices.Comment: CIDR 200

Data Degradation: Making Private Data Less Sensitive Over Time

Trail disclosure is the leakage of privacy sensitive data, resulting from negligence, attack or abusive scrutinization or usage of personal digital trails. To prevent trail disclosure, data degradation is proposed as an alternative to the limited retention principle. Data degradation is based on the assumption that long lasting purposes can often be satisfied with a less accurate, and therefore less sensitive, version of the data. Data will be progressively degraded such that it still serves application purposes, while decreasing accuracy and thus privacy sensitivity

uFLIP: Understanding the Energy Consumption of Flash Devices

International audienceUnderstanding the energy consumption of flash devices is important for two reasons. First, energy is emerging as a key metric for data management systems. It is thus important to understand how we can reason about the energy consumption of flash devices beyond their approximate aggregate consumption (low power consumption in idle mode, average Watt consumption from the data sheets). Second, when measured at a sufficiently fine granularity, the energy consumption of a given device might complement the performance characteristics derived from its response time profile. Indeed, background work which is not directly observable with a response time profile appears clearly when energy is used as a metric. In this paper, we discuss the results from the uFLIP benchmark applied to four different SSD devices using both response time and energy as metric

Fairness concerns in digital right management models

International audienceDigital piracy is threatening the global multimedia content industry and blindly applied coercive Digital Right Management (DRM) policies do nothing but legitimise this piracy. This paper presents new software and hardware infrastructure aimed at reconciling the content providers' and consumers' points of view by giving the ability to develop fair business models (i.e., that preserve the interest of both parties). The solution is based on the use of tamper-resistant devices (smart cards) to securely store sensitive data (e.g., personal consumer data or data expressing the terms of a B2C contract or licence) and to perform the computation required by a contract/licence activation. In other words, smart cards can be seen as tamper-resistant Service Level Agreement (SLA) enablers

SGBD embarqué dans une puce : retour d'expérience

National audienceLa carte à puce est aujourd'hui l'objet portable sécurisé le plus répandu. Il y a 4 ans, nous avons jeté les bases d'une étude portant sur l'embarquement de techniques bases de données dans une carte à puce. Cette étude a conduit à la définition de principes de conception pour ce que nous avons appelé alors PicoDBMS, un système de gestion de bases de données (SGBD) complet intégré dans une carte à puce. Depuis, grâce au progrès du matériel et aux efforts conjoints de notre équipe et de notre partenaire industriel, les principes définis initialement ont donné naissance à un prototype complet tournant sur une plate-forme carte à puce expérimentale. Cet article reconsidère la formulation du problème initial à la lumière des évolutions matérielles et applicatives. Il introduit ensuite un banc d'essai dédié aux bases de données embarquées dans des puces et présente une analyse de performance détaillée de notre prototype. Enfin, il dresse des perspectives de recherche dans le domaine de la gestion de données dans les puces sécurisées

The Life-Cycle Policy model

Our daily life activity leaves digital trails in an increasing number of databases (commercial web sites, internet service providers, search engines, location tracking systems, etc). Personal digital trails are commonly exposed to accidental disclosures resulting from negligence or piracy and to ill-intentioned scrutinization and abusive usages fostered by fuzzy privacy policies. No one is sheltered because a single event (e.g., applying for a job or a credit) can suddenly make our history a precious asset. By definition, access control fails preventing trail disclosures, motivating the integration of the Limited Data Retention principle in legislations protecting data privacy. By this principle, data is withdrawn from a database after a predefined time period. However, this principle is difficult to apply in practice, leading to retain useless sensitive information for years in databases. In this paper, we propose a simple and practical data degradation model where sensitive data undergoes a progressive and irreversible degradation from an accurate state at collection time, to intermediate but still informative degraded states, up to complete disappearance when the data becomes useless. The benefits of data degradation is twofold: (i) by reducing the amount of accurate data, the privacy offence resulting from a trail disclosure is drastically reduced and (ii) degrading the data in line with the application purposes offers a new compromise between privacy preservation and application reach. We introduce in this paper a data degradation model, analyze its impact over core database techniques like storage, indexation and transaction management and propose degradation-aware techniques

Smart Card DBMS: where are we now?

Smart card is today the most widespread secured portable computing device. Four years ago, we addressed the problem of scaling down database techniques for the smart card and we proposed the design of what we called a PicoDBMS, a full-fledged database system embedded in a smart card. Since then, thanks to the hardware progress and to the joint implementation efforts of our team and our industrial partner, this utopian design gave birth to a complete prototype running on an experimental smart card platform. This paper revisits the problem statement in the light of the hardware and applications evolution. Then, it introduces a benchmark dedicated to Pico–style databases and provides an extensive performance analysis of our prototype, discussing lessons learned at experimentation time and helping selecting the appropriate storage and indexation model for a given class of embedded applications. Finally, it draws new research perspectives for data management on secured chips (smart cards, USB dongles, multimedia rendering devices, smart objects in an ambient intelligence surrounding)

SEP2P: Secure and Efficient P2P Personal Data Processing

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