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Detail
Conference Paper
Transform-based Lossy Compression for HPC Big Datasets
- Authors
- Aekyung Moon, Juyoung Park, Yun Jeong Song
- Issue Date
- 2021-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2021, pp.1345-134
- Language
- English
- Type
- Conference Paper
- Project Code
- 21JD1100, Flexible printing electronics New electronics industry technology development, Moon Ae Kyeung
- Abstract
- As many IoT devices generate an enormous and varied amount of data that need to be processed in a brief space of time, storing and processing IoT big data becomes a huge challenge. While lossy compression can drastically reduce data volume, finding an optimal balance between volume reduction and information loss is not an easy task. Motivated by this, we analyze the characteristics of data compressed and present relationships between compression ratio and data characteristics to use an effective lossy compression algorithms.
- KSP Keywords
- Big Data, Compression Algorithm, Data Volume, Data characteristics, Information Loss, IoT Devices, Lossy Compression, Volume reduction, compression ratio