Change a Bit to save Bytes: Compression for Floating Point Time-Series Data

• DOI: 10.48550/arxiv.2303.04478
• Publication Date: 2023-01-01
• Authors: Francesco Taurone; Daniel E. Lucani; Marcell Fehér; Qi Zhang
• Keywords: Lossy compression

The number of IoT devices is expected to continue its dramatic growth in the coming years and, with it, a amount data be transmitted, processed and stored. Compression techniques that support analytics directly on compressed could pave way for systems scale efficiently these growing demands. This paper proposes two novel methods preprocessing stream floating point improve compression capabilities various compressors. In particular, are shown helpful recent compressors allow random access while maintaining good compression. Our reductions up 80% when allowing at most 1% recovery error.