Delegation sketch: a parallel design with support for fast and accurate concurrent operations
Charalampos Stylianopoulos, Ivan Walulya, Magnus Almgren, Olaf Landsiedel, Marina Papatriantafilou
Abstract
Sketches are data structures designed to answer approximate queries by trading memory overhead with accuracy guarantees. More specifically, sketches efficiently summarize large, high-rate streams of data and quickly answer queries on these summaries. In order to support such high throughput rates in modern architectures, parallelization and support for fast queries play a central role, especially when monitoring unpredictable data that can change rapidly as, e.g., in network monitoring for large-scale denial-of-service attacks. However, most existing parallel sketch designs have focused either on high insertion rate or on high query rate, and fail to support cases when these operations are concurrent.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get 1fdb39c2-6eac-42d8-bfd0-c3b9d04d9d22Cited by top-tier papers2
- MOST: Model-Based Compression with Outlier Storage for Time Series DataZehai Yang, Shimin ChenSIGMOD 2024 · 9 citations
- Cuckoo Heavy Keeper and the balancing act of maintaining heavy hitters in stream processingVinh Quang Ngo, Marina PapatriantafilouVLDB 2025 · 2 citations
Related papers
- Fast concurrent data sketchesArik Rinberg, Alexander Spiegelman, Edward Bortnikov, Eshcar Hillel et al.PPoPP 2020 · 4 citations
- Optimistic Data Parallelism for FPGA-Accelerated SketchingMartin Kiefer, Ilias Poulakis, Eleni Tzirita Zacharatou, Volker MarklVLDB 2023 · 11 citations
- OctoSketch: Enabling Real-Time, Continuous Network Monitoring over Multiple CoresYinda Zhang, Peiqing Chen, Zaoxing LiuNSDI 2024 · 18 citations
- On the algebra of data sketchesJakub LemieszVLDB 2021 · 21 citations
- Spatiotemporal Sketch Disaggregation: Streaming Analytics with Heterogeneous ResourcesJonatan Langlet, Peiqing Chen, Michael Mitzenmacher, Zaoxing Liu et al.ICDE 2026
