Beomseok Noh

Recent interest in persistent memory (PM) has stirred development of index structures that are efficient in PM. Recent such developments have all focused on variations of the B-tree. In this paper, we show that the radix tree, which is another less popular indexing structure, can be more appropriate as an efficient PM indexing structure. This is because the radix tree structure is determined by the prefix of the inserted keys and also does not require tree rebalancing operations and node granula

Emerging byte-addressable non-volatile memory is considered an alternative storage device for database logs that require persistency and high performance. In this work, we develop NVWAL (NVRAM Write-Ahead Logging) for SQLite. The contribution of NVWAL consists of three elements: (i) byte-granularity differential logging that effectively eliminates the excessive I/O overhead of filesystem-based logging or journaling, (ii) transaction-aware lazy synchronization that reduces cache synchronization o

This paper investigates how to leverage emerging byteaddressable persistent memory (PM) to enhance the performance of key-value (KV) stores. We present a novel KV store, the Single-Level Merge DB (SLM-DB), which takes advantage of both the B+-tree index and the Log-Structured Merge Trees (LSM-tree) approach by making the best use of fast persistent memory. Our proposed SLM-DB achieves high read performance as well as high write performance with low write amplification and near-optimal read ampli

Low latency storage media such as byte-addressable persistent memory (PM) requires rethinking of various data structures in terms of optimization. One of the main challenges in implementing hash-based indexing structures on PM is how to achieve efficiency by making effective use of cachelines while guaranteeing failure-atomicity for dynamic hash expansion and shrinkage. In this paper, we present Cacheline-Conscious Extendible Hashing (CCEH) that reduces the overhead of dynamic memory block manag

Misaligned interaction between SQLite and EXT4 of Android I/O stack yields excessive random writes. In this work, we developed multi-version B-tree with lazy split (LS-MVBT) to effectively address Journaling of Journal anomaly in Android I/O. LS-MVBT is carefully crafted to minimize write traffic caused by fsync() of SQLite. The contribution of LS-MVBT consists of two key elements: (i) Multi-version B-tree effectively reduces the number of fsync() calls via weaving crash recovery information wit

The slotted-page structure is a database page format commonly used for managing variable-length records. In this work, we develop a novel "failure-atomic slotted page structure" for persistent memory that leverages byte addressability and durability of persistent memory to minimize redundant write operations used to maintain consistency in traditional database systems. Failure-atomic slotted paging consists of two key elements: (i) in-place commit per page using hardware transactional memory and

This work is dedicated to resolve the Journaling of Journal Anomaly in Android IO stack. We orchestrate SQLite and EXT4 filesystem so that SQLite's file-backed journaling activity can dispense with the expensive filesystem intervention, the journaling, without compromising the file integrity under unexpected filesystem failure. In storing the logs, we exploit the direct IO to suppress the filesystem interference. This work consists of three key ingredients: (i) Preallocation with Explicit Journa

Desktop grids use opportunistic sharing to exploit large collections of personal computers and workstations across the Internet, achieving tremendous computing power at low cost. Traditional desktop grid systems are typically based on a client-server architecture, which has inherent shortcomings with respect to robustness, reliability and scalability. In this paper, we propose a decentralized, robust, highly available, and scalable infrastructure to match incoming jobs to available resources. Th

Applications that query into very large multidimensional datasets are becoming more common. Many self-describing scientific data file formats have also emerged, which have structural metadata to help navigate the multi-dimensional arrays that are stored in the files. The files may also contain application-specific semantic metadata. In this paper, we discuss efficient methods for performing searches for subsets of multi-dimensional data objects, using semantic information to build multidimension

While declustering methods for distributed multidimensional indexing of large datasets have been researched widely in the past, replication techniques for multidimensional indexes have not been investigated deeply. In general, a centralized index server may become the performance bottleneck in a wide area network rather than the data servers, since the index is likely to be accessed more often than any of the datasets in the servers. In this paper, we present two different multidimensional index

Scientific applications that query into very large multidimensional datasets are becoming more common. These datasets are growing in size every day, and are becoming truly enormous, making it infeasible to index individual data elements. We have instead been experimenting with chunking the datasets to index them, grouping data elements into small chunks of a fixed, but dataset-specific, size to take advantage of spatial locality. While spatial indexing structures based on R-trees perform reasona

Grid computing and Peer-to-peer (P2P) systems are emerging as new paradigms for managing large scale distributed resources across wide area networks. While Grid computing focuses on managing heterogeneous resources and relies on centralized managers for resource and data discovery, P2P systems target scalable, decentralized methods for publishing and searching for data. In large distributed systems, a centralized resource manager is a potential performance bottleneck. Decentralization can help a