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<p>The past decade has seen wide availability of solid-state drives (SSDs) in settings ranging from personal computing to enterprise storage. Their success over the hard disks is driven by performance considerations and cost savings. Besides SSDs based on flash memory, there have been ongoing efforts in developing other non-volatile memory technologies such as phase-change memory and MRAM. All these technologies enable what we refer to as random-access block devices. Unlike hard disks, these devices have fast random accesses; on the other hand, their writes are more expensive than their reads. In this work, we study how to optimize database and storage algorithms for the I/O characteristics of random-access block devices. Specifically, we tackle the following three problems.</p><p>The first one is about permuting data out-of-core. While external merge sort is popular for implementing permutation on hard disks, it carries unnecessary overhead in storing and comparing keys. We propose more efficient algorithms for a useful class of permutations called Address-Digit Permutations on random-access block devices.</p><p>The second problem is concurrency control for indexes on SSDs. Various indexes have been proposed for these devices, but to make such indexes practical, we must address the issue of concurrency control. We propose a novel indexing and concurrency control scheme which allows concurrent accesses during ongoing index reorganizations, and does so with minimal memory and block-level locking.</p><p>The third problem concerns log-structured merge, a popular indexing technique well-suited to random-access block devices. We show how an intelligent partial merge policy, combined with a block-preserving merge procedure, can ­significantly lower write traffic while preserving other advantages of log-structured merge.</p> / Dissertation

La capacité des systèmes de stockage de données ne cesse de croître pour atteindre actuellement l’échelle de l’exaoctet, ce qui a un réel impact sur la robustesse des systèmes de stockage. En effet, plus le nombre de disques contenus dans un système est grand, plus il est probable d’y avoir une défaillance. De même, le temps de la reconstruction d’un disque est proportionnel à sa capacité. La simulation permet le test de nouveaux mécanismes dans des conditions quasi réelles et de prédire leur comportements. Open and Generic data Storage system Simulation tool (OGSSim), l’outil que nous proposons, supporte l’hétérogénéité et la taille importante des systèmes actuels. Sa décomposition modulaire permet d’entreprendre chaque technologie de stockage, schéma de placement ou modèle de calcul comme des briques pouvant être combinées entre elles pour paramétrer au mieux la simulation. La robustesse étant un paramètre critique dans ces systèmes, nous utilisons le declustered RAID pour assurer la distribution de la reconstruction des données d’un disque en cas de défaillance. Nous proposons l’algorithme Symmetric Difference of Source Sets (SD2S) qui utilise le décalage des blocs de données pour la création du schéma de placement. Le pas du décalage est issu du calcul de la proximité des ensembles de provenance logique des blocs d’un disque physique. Pour évaluer l’efficacité de SD2S, nous l’avons comparé à la méthode Crush, exemptée des réplicas. Il en résulte que la création du schéma de placement, aussi bien en mode normal qu’en mode défaillant, est plus rapide avec SD2S, et que le coût en espace mémoire est également réduit (nul en mode normal). En cas de double défaillance, SD2S assure la sauvegarde d’une partie, voire de la totalité, des données / Capacity of data storage systems does not cease to increase to currently reach the exabyte scale. This observation gets a real impact on storage system robustness. In fact, the more the number of disks in a system is, the greater the probability of a failure happening is. Also, the time used for a disk reconstruction is proportional to its size. Simulation is an appropriate technique to test new mechanisms in almost real conditions and predict their behavior. We propose a new software we callOpen and Generic data Storage system Simulation tool (OGSSim). It handles the heterogeneity andthe large size of these modern systems. Its modularity permits the undertaking of each storage technology, placement scheme or computation model as bricks which can be added and combined to optimally configure the simulation.Robustness is a critical issue for these systems. We use the declustered RAID to distribute the data reconstruction in case of a failure. We propose the Symmetric Difference of Source Sets (SD2S) algorithmwhich uses data block shifhting to achieve the placement scheme. The shifting offset comes from the computation of the distance between logical source sets of physical disk blocks. To evaluate the SD2S efficiency, we compared it to Crush method without replicas. It results in a faster placement scheme creation in normal and failure modes with SD2S and in a significant reduced memory space cost (null without failure). Furthermore, SD2S ensures the partial, if not total, reconstruction of data in case of multiple failures.

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