Demonstrating Waffle: A Self-Driving Grid Index-Reference-Cited by-同舟云学术

Demonstrating Waffle: A Self-Driving Grid Index

Published:2023-08 Issue:12 Volume:16 Page:3954-3957
ISSN:2150-8097
Container-title:Proceedings of the VLDB Endowment
language:en
Short-container-title:Proc. VLDB Endow.

Author:

Choi Dalsu¹,Yoon Hyunsik¹,Lee Hyubjin¹,Chung Yon Dohn¹

Affiliation:

1. Korea University, Seoul, Korea

Abstract

This paper demonstrates Waffle, a self-driving grid indexing system for moving objects. We introduce system architecture, system workflow, and user scenarios. Waffle enables the management of moving objects with less human effort while automatically improving performance.

Publisher

Association for Computing Machinery (ACM)

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Link

https://dl.acm.org/doi/pdf/10.14778/3611540.3611594

Reference12 articles.

1. Dana Van Aken , Andrew Pavlo , Geoffrey J. Gordon , and Bohan Zhang . 2017 . Automatic Database Management System Tuning Through Large-scale Machine Learning. In SIGMOD 2017. ACM, 1009--1024. Dana Van Aken, Andrew Pavlo, Geoffrey J. Gordon, and Bohan Zhang. 2017. Automatic Database Management System Tuning Through Large-scale Machine Learning. In SIGMOD 2017. ACM, 1009--1024.

2. An inquiry into machine learning-based automatic configuration tuning services on real-world database management systems

3. Waffle

4. Ahmed Eldawy and Mohamed F . Mokbel . 2019 . Roads and streets around the world each represented as individual line segments. Retrieved from UCR-STAR https://star.cs.ucr.edu/?OSM2015/road-network, last access: 06/24/2023. Ahmed Eldawy and Mohamed F. Mokbel. 2019. Roads and streets around the world each represented as individual line segments. Retrieved from UCR-STAR https://star.cs.ucr.edu/?OSM2015/road-network, last access: 06/24/2023.