T <scp>EQ</scp> : An Open and Developer-friendly Testbed for Edge-based Query Processing Algorithms

Edge computing is ideally suited for querying populations of fast data streams. However, developing and evaluating edge-based query processing algorithms is challenging due to the decentralized setting and the lack of effective tools. For example, current simulators fail to execute real queries. To rectify these shortcomings, we propose TeQ, a testbed for edge-based query processing algorithms, designed expressly to be open, enabling extensible simulation and algorithm deployment, and to be developer-friendly, simplifying otherwise cumbersome simulation, complex algorithm management, and tedious evaluation. TeQ encompasses novel techniques to achieve these capabilities, including (1) a streamlined framework for implementing decentralized algorithms as modular, Docker-based executables; (2) data and query playback controls to enable reproducible and consistent evaluations; and (3) mechanisms for transforming runtime metrics into system-wide metrics desired by algorithm developers.

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Publication Details

Published
2025-06-17
DOI
https://doi.org/10.1145/3722212.3725138
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

T EQ : An Open and Developer-friendly Testbed for Edge-based Query Processing Algorithms

Christian S. Jensen, Hua Lu, X. S. Jiang, Huan Li et al.
IoT and Edge/Fog Computing
article

T EQ : An Open and Developer-friendly Testbed for Edge-based Query Processing Algorithms

Christian S. Jensen, Hua Lu, X. S. Jiang, Huan Li, Bo Tang, Yu Lei
article en

Abstract

Edge computing is ideally suited for querying populations of fast data streams. However, developing and evaluating edge-based query processing algorithms is challenging due to the decentralized setting and the lack of effective tools. For example, current simulators fail to execute real queries. To rectify these shortcomings, we propose TeQ, a testbed for edge-based query processing algorithms, designed expressly to be open, enabling extensible simulation and algorithm deployment, and to be developer-friendly, simplifying otherwise cumbersome simulation, complex algorithm management, and tedious evaluation. TeQ encompasses novel techniques to achieve these capabilities, including (1) a streamlined framework for implementing decentralized algorithms as modular, Docker-based executables; (2) data and query playback controls to enable reproducible and consistent evaluations; and (3) mechanisms for transforming runtime metrics into system-wide metrics desired by algorithm developers.

Southern University of Science and Technology (CN), Zhejiang University (CN), Aalborg University (DK)
Openalex Percentile: Top 85%
IoT and Edge/Fog Computing
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