Name
Abstract | ||
|---|---|---|
Most data intensive applications often access only a few fields of the objects they are operating on. Since NVM provides fast, byte-addressable access to durable memory, it is possible to access various fields of an object stored in NVM directly without incurring any serialization and deserialization cost. This paper proposes a novel tiered object storage model that modifies a data structure such that only a chosen subset of fields of the data structure are stored in NVM, while the remaining fields are stored in a cheaper (and a traditional) storage layer such as HDDs/SSDs. We introduce a novel linear-programming based optimization framework for deciding the field placement. Our proof of concept demonstrates that a tiered object storage model improves the execution time of standard operations by up to 50% by avoiding the cost of serialization/deserialization and by reducing the memory footprint of operations. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Distributed, Parallel, and Cluster Computing | Data structure,Object storage,Serialization,Computer science,Proof of concept,Execution time,Memory footprint,Embedded system,Distributed computing |
DocType | Volume | Citations |
Journal | abs/1807.06417 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Johnu George | 1 | 0 | 0.68 |
| Ramdoot Pydipaty | 2 | 0 | 0.68 |
| Xinyuan Huang | 3 | 1 | 0.71 |
| Amit Saha | 4 | 0 | 1.01 |
| Debo Dutta | 5 | 14 | 2.15 |
| Gary Wang | 6 | 9 | 2.86 |
| Uma Gangumalla | 7 | 0 | 0.34 |