A Cost-Saving Response Scheduler for Highway Structural Health Monitoring Data Applications

Abstract In the process of responding to user applications on the highway structural health monitoring data sharing platforms, the objective is to decrease the network transmission costs and avoid a mass of redundant Input/Output operations between the storage server and local hard disks. Since none of existing job scheduling and structural health monitoring data analysis research has focused on this topic, we study the problem of cost-saving response scheduling for highway structural health monitoring data applications. To solve this problem, we develop a greedy response scheduler with (1+ $$\frac{1}{e-1})$$ -approximation ratio. Evaluation results demonstrate the effectiveness and efficiency of our proposed solution.

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Publication Details

Journal
Data Science and Engineering
Published
2025-11-13
DOI
https://doi.org/10.1007/s41019-025-00314-w
Primary Topic
Real-Time Systems Scheduling
Type
article
Field-Weighted Citation Impact
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article

A Cost-Saving Response Scheduler for Highway Structural Health Monitoring Data Applications

Zejiao Dong, Hongzhi Wang, Zhenlong Chao, Yulin Wang et al.
Data Science and Engineering
Real-Time Systems Scheduling
article

A Cost-Saving Response Scheduler for Highway Structural Health Monitoring Data Applications

Zejiao Dong, Hongzhi Wang, Zhenlong Chao, Yulin Wang, Zhixin Qi
article en

Abstract

Abstract In the process of responding to user applications on the highway structural health monitoring data sharing platforms, the objective is to decrease the network transmission costs and avoid a mass of redundant Input/Output operations between the storage server and local hard disks. Since none of existing job scheduling and structural health monitoring data analysis research has focused on this topic, we study the problem of cost-saving response scheduling for highway structural health monitoring data applications. To solve this problem, we develop a greedy response scheduler with (1+ $$\frac{1}{e-1})$$ -approximation ratio. Evaluation results demonstrate the effectiveness and efficiency of our proposed solution.

Data Science and EngineeringVol. 11(1)
Harbin Institute of Technology (CN), Heilongjiang Institute of Technology (CN)
Openalex Percentile: Top 63%
Real-Time Systems Scheduling
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A Cost-Saving Response Scheduler for Highway Structural Health Monitoring Data Applications — Zejiao Dong, Hongzhi Wang, et al. · Data Science and Engineering (2025) | TGRS Research Map | TGRS