117 citations · 361 across the 41 of their papers we have counts for
5 papers · 1 filter
EntroGD: Scalable Generalized Deduplication for Efficient Direct Analytics on Compressed IoT Data
Xiaobo Zhao, Daniel E. Lucani
Massive data streams from IoT and cyber-physical systems must be processed under strict bandwidth, latency, and resource constraints. Generalized Deduplication (GD) is a promising…
PairwiseHist: Fast, Accurate and Space-Efficient Approximate Query Processing with Data Compression
Aaron Hurst, Daniel E. Lucani, Qi Zhang
Exponential growth in data collection is creating significant challenges for data storage and analytics latency.Approximate Query Processing (AQP) has long been touted as a solutio…
Lossless preprocessing of floating point data to enhance compression
Francesco Taurone, Daniel E. Lucani, Marcell Fehér +1
Data compression algorithms typically rely on identifying repeated sequences of symbols from the original data to provide a compact representation of the same information, while ma…
GreedyGD: Enhanced Generalized Deduplication for Direct Analytics in IoT
Aaron Hurst, Daniel E. Lucani, Qi Zhang
Exponential growth in the amount of data generated by the Internet of Things currently pose significant challenges for data communication, storage and analytics and leads to high c…
An Adaptive Column Compression Family for Self-Driving Databases
Marcell Fehér, Daniel E. Lucani, Ioannis Chatzigeorgiou
Modern in-memory databases are typically used for high-performance workloads, therefore they have to be optimized for small memory footprint and high query speed at the same time.…