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Flexible Online Task Assignment in Real-Time Spatial Data

Summary: Defines Flexible Two-sided Online task Assignment (FTOA) for real-time spatial data, guiding idle workers via predicted task/worker distributions to boost matches. Two-step framework combines offline prediction with POLAR-OP online assignment; achieves 0.47-competitive ratio and O(1) per-event processing, validated on synthetic and real taxi data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11607
Venue
VLDB
Year
2017
Pagerank
5.093636e-05
Overall Rank
11,998 | 17.69%
DOI
10.14778/3137628.3137643

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Authors

BibTeX Citation

@article{tong_vldb17,
        title = {{Flexible Online Task Assignment in Real-Time Spatial Data}},
        author = {Tong, Yongxin and Wang, Libin and Zhou, Zimu and Ding, Bolin and Chen, Lei and Ye, Jieping and Xu, Ke},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {11},
        pages = {1334},
        doi = {10.14778/3137628.3137643},
        url = {https://doi.org/10.14778/3137628.3137643},
        year = {2017}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
2,327 Capacity Constrained Assignment in Spatial Databases 2008 SIGMOD 8.7476945e-05
2,349 On Efficient Spatial Matching 2007 VLDB 8.7115756e-05
2,780 A Framework for Protecting Worker Location Privacy in Spatial Crowdsourcing 2014 VLDB 8.1294906e-05
4,661 Online Minimum Matching in Real-Time Spatial Data: Experiments and Analysis 2016 VLDB 6.5792798e-05
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