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Abstract-Archival storage systems for scientific data have been growing in both size and relevance over the past two decades, yet researchers and system designers alike must rely on limited and obsolete knowledge to guide archival management and design. To address this issue, we analyzed three years of filelevel activities from the NCAR mass storage system, providing valuable insight into a large-scale scientific archive with over 1600 users, tens of millions of files, and petabytes of data.Our examination of system usage showed that, while a subset of users were responsible for most of the activity, this activity was widely distributed at the file level. We also show that the physical grouping of files and directories on media can improve archival storage system performance. Based on our observations, we provide suggestions and guidance for both future scientific archival system designs as well as improved tracing of archival activity.

Abstract-Maintaining information privacy is challenging when sharing data across a distributed long-term datastore. In such applications, secret splitting the data across independent sites has been shown to be a superior alternative to fixed-key encryption; it improves reliability, reduces the risk of insider threat, and removes the issues surrounding key management. However, the inherent security of such a datastore normally precludes it from being directly searched without reassembling the data; this, however, is neither computationally feasible nor without risk since reassembly introduces a single point of compromise. As a result, the secret-split data must be pre-indexed in some way in order to facilitate searching. Previously, fixed-key encryption has also been used to securely pre-index the data, but in addition to key management issues, it is not well suited for long term applications.To meet these needs, we have developed Percival: a novel system that enables searching a secret-split datastore while maintaining information privacy. We leverage salted hashing, performed within hardware security modules, to access prerecorded queries that have been secret split and stored in a distributed environment; this keeps the bulk of the work on each client, and the data custodians blinded to both the contents of a query as well as its results. Furthermore, Percival does not rely on the datastore's exact implementation. The result is a flexible design that can be applied to both new and existing secret-split datastores. When testing Percival on a corpus of approximately one million files, it was found that the average search operation completed in less than one second.

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This thesis addresses the problem of contention management in Software Transactional Memory (STM), which is a scheme for managing shared memory in a concurrent programming environment. STM views shared memory in a way similar to that of a database; read and write operations are handled through transactions, with changes to the shared memory becoming permanent through commit operations. Research on this subject reveals that there are currently varying methods for collision detection, data validation, and contention management, each of which has different situations in which they become the preferred method. This thesis introduces a dynamic contention manager that monitors current performance and chooses the proper contention manager accordingly. Performance calculations, and subsequent polling of the underlying library, are minimized. As a result, this adaptive contention manager yields a higher average performance level over time when compared with existing static implementations.