Optimizing Edge-Based Query Processing for Real-Time Applications

Kalgi Gandhi, Minal Bhise

2025

Abstract

The rapid growth of edge devices in large-scale systems presents challenges due to limited processing power, memory, and bandwidth. Efficient resource utilization and data management during query processing are critical, especially for costly join operations. The Column Imprint-Hash Join (CI-HJ) accelerates hash joins using equi-height binning but lacks real-time efficiency and scans unnecessary cachelines. This paper introduces Workload Aware Column Imprint-Hash Join (WACI-HJ), a novel approach that leverages workload prediction to optimize hash joins for real-time edge query processing. WACI-HJ comprises of two phases: the WACI-HJ Generation Phase predicts query workloads and pre-processes data into bins using blocking and hashing techniques, reducing overhead before query arrival. The Query Processing and Resource Utilization Phase efficiently utilizes CPU, RAM, and I/O resources for runtime processing. Evaluations using Benchmark and Real-World datasets demonstrate significant improvements in the Percentage of Cachelines Read PCR, Query Execution Time QET, and Resource Utilization. PCR and QET show 18% and 5% improvement respectively. The proposed technique has been demonstrated to work well for scaled and skewed data. Although PCR is an indirect measure of energy consumption, direct Energy-Efficiency Experiments reveal gains of 1%, 23%, and 18% in CPU, RAM, and I/O utilization respectively. WACI-HJ provides an optimal and sustainable solution for edge database management.

Paper Citation

in Harvard Style

Gandhi K. and Bhise M. (2025). Optimizing Edge-Based Query Processing for Real-Time Applications. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 259-266. DOI: 10.5220/0013289300003929

in Bibtex Style

@conference{iceis25,
author={Kalgi Gandhi and Minal Bhise},
title={Optimizing Edge-Based Query Processing for Real-Time Applications},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={259-266},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013289300003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Optimizing Edge-Based Query Processing for Real-Time Applications
SN - 978-989-758-749-8
AU - Gandhi K.
AU - Bhise M.
PY - 2025
SP - 259
EP - 266
DO - 10.5220/0013289300003929
PB - SciTePress