Towards Design and Analysis For High-Performance and Reliable SSDs

NAND Flash-based Solid State Disks have many attractive technical merits, such as low power consumption, light weight, shock resistance, sustainability of hotter operation regimes, and extraordinarily high performance for random read access, which makes SSDs immensely popular and be widely employed in different types of environments including portable devices, personal computers, large data centers, and distributed data systems. However, current SSDs still suffer from several critical inherent limitations, such as the inability of in-place-update, asymmetric read and write performance, slow garbage collection processes, limited endurance, and degraded write performance with the adoption of MLC and TLC techniques. To alleviate these limitations, we propose optimizations from both specific outside applications layer and SSDs\u27 internal layer. Since SSDs are good compromise between the performance and price, so SSDs are widely deployed as second layer caches sitting between DRAMs and hard disks to boost the system performance. Due to the special properties of SSDs such as the internal garbage collection processes and limited lifetime, traditional cache devices like DRAM and SRAM based optimizations might not work consistently for SSD-based cache. Therefore, for the outside applications layer, our work focus on integrating the special properties of SSDs into the optimizations of SSD caches. Moreover, our work also involves the alleviation of the increased Flash write latency and ECC complexity due to the adoption of MLC and TLC technologies by analyzing the real work workloads

Study On Endurance Of Flash Memory Ssds

Flash memory promises to revolutionize storage systems because of its massive performance gains, ruggedness, large decrease in power usage and physical space requirements, but it is not a direct replacement for magnetic hard disks. Flash memory possesses fundamentally different characteristics and in order to fully utilize the positive aspects of flash memory, we must engineer around its unique limitations. The primary limitations are lack of in-place updates, the asymmetry between the sizes of the write and erase operations, and the limited endurance of flash memory cells. This leads to the need for efficient methods for block cleaning, combating write amplification and performing wear leveling. These are fundamental attributes of flash memory and will always need to be understood and efficiently managed to produce an efficient and high performance storage system. Our goal in this work is to provide analysis and algorithms for efficiently managing data storage for endurance in flash memory. We present update codes, a class of floating codes, which encodes data updates as flash memory cell increments that results in reduced block erases and longer lifespan of flash memory, and provides a new algorithm for constructing optimal floating codes. We also analyze the theoretically possible limits of write amplification reduction and minimization by using offline workloads. We give an estimation of the minimal write amplification by a workload decomposition algorithm and find that write amplification can be pushed to zero with relatively low over-provisioning. Additionally, we give simple, efficient and practical algorithms that are effective in reducing write amplification and performing wear leveling. Finally, we present a quantitative model of wear levels in flash memory by constructing a difference equation that gives erase counts of a block with workload, wear leveling strategy and SSD configuration as parameters

Préserver la vie privée des individus grâce aux Systèmes Personnels de Gestion des Données

Riding the wave of smart disclosure initiatives and new privacy-protection regulations, the Personal Cloud paradigm is emerging through a myriad of solutions offered to users to let them gather and manage their whole digital life. On the bright side, this opens the way to novel value-added services when crossing multiple sources of data of a given person or crossing the data of multiple people. Yet this paradigm shift towards user empowerment raises fundamental questions with regards to the appropriateness of the functionalities and the data management and protection techniques which are offered by existing solutions to laymen users. Our work addresses these questions on three levels. First, we review, compare and analyze personal cloud alternatives in terms of the functionalities they provide and the threat models they target. From this analysis, we derive a general set of functionality and security requirements that any Personal Data Management System (PDMS) should consider. We then identify the challenges of implementing such a PDMS and propose a preliminary design for an extensive and secure PDMS reference architecture satisfying the considered requirements. Second, we focus on personal computations for a specific hardware PDMS instance (i.e., secure token with mass storage of NAND Flash). In this context, we propose a scalable embedded full-text search engine to index large document collections and manage tag-based access control policies. Third, we address the problem of collective computations in a fully-distributed architecture of PDMSs. We discuss the system and security requirements and propose protocols to enable distributed query processing with strong security guarantees against an attacker mastering many colluding corrupted nodes.Surfant sur la vague des initiatives de divulgation restreinte de données et des nouvelles réglementations en matière de protection de la vie privée, le paradigme du Cloud Personnel émerge à travers une myriade de solutions proposées aux utilisateurs leur permettant de rassembler et de gérer l'ensemble de leur vie numérique. Du côté positif, cela ouvre la voie à de nouveaux services à valeur ajoutée lors du croisement de plusieurs sources de données d'un individu ou du croisement des données de plusieurs personnes. Cependant, ce changement de paradigme vers la responsabilisation de l'utilisateur soulève des questions fondamentales quant à l'adéquation des fonctionnalités et des techniques de gestion et de protection des données proposées par les solutions existantes aux utilisateurs lambda. Notre travail aborde ces questions à trois niveaux. Tout d'abord, nous passons en revue, comparons et analysons les alternatives de cloud personnel au niveau des fonctionnalités fournies et des modèles de menaces ciblés. De cette analyse, nous déduisons un ensemble général d'exigences en matière de fonctionnalité et de sécurité que tout système personnel de gestion des données (PDMS) devrait prendre en compte. Nous identifions ensuite les défis liés à la mise en œuvre d'un tel PDMS et proposons une conception préliminaire pour une architecture PDMS étendue et sécurisée de référence répondant aux exigences considérées. Ensuite, nous nous concentrons sur les calculs personnels pour une instance matérielle spécifique du PDMS (à savoir, un dispositif personnel sécurisé avec un stockage de masse de type NAND Flash). Dans ce contexte, nous proposons un moteur de recherche plein texte embarqué et évolutif pour indexer de grandes collections de documents et gérer des politiques de contrôle d'accès basées sur des étiquettes. Troisièmement, nous abordons le problème des calculs collectifs dans une architecture entièrement distribuée de PDMS. Nous discutons des exigences d'architectures système et de sécurité et proposons des protocoles pour permettre le traitement distribué des requêtes avec de fortes garanties de sécurité contre un attaquant maîtrisant de nombreux nœuds corrompus

MRAM commercialization potential evaluation Research Based on the Chinese Market

Regarding the Chinese data storage industries, there is an urgent need for a national strategy and new investments as there are new technologies emerging in the global markets. The storage technology commercialization activities are becoming a widespread concern for the Chinese government and their strategic enterprises. The promotion of storage technology commercialization has become a common goal for enterprise and national government strategies. How the potential for commercialization of a storage technology can be assessed, what evaluation index should be used, and what the factors affect the storage technology are the important issues that must be addressed