Towards Real-Time Data Ingestion for Industrial Internet of Things
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-5575-2_38
Reference5 articles.
1. Gong, C., et al: Causal discovery from temporal data. In: SIGKDD, pp. 5803–5804 (2023)
2. Li, Y., Chen, W., Ding, Y., Qie, Y., Zhang, C.: A vision of intelligent IoT - trends, characteristics and functional architecture. In: IWCMC, pp. 184–189 (2022)
3. Lepping, A., et al.: Showcasing data management challenges for future IoT applications with NebulaStream. In: PVLDB, pp. 3930–3933 (2023)
4. Fang, C., Song, S., Guan, H., Huang, X., Wang, C., Wang, J.: Grouping time series for efficient columnar storage. In: Proceedings of the ACM on Management of Data, vol. 26 (2023)
5. Yan, Y., Zheng, B., Wang, H., Zhang, J., Wang, Y.: CnosDB: a flexible distributed time-series database for large-scale data. In: Wang, X., et al. Database Systems for Advanced Applications, DASFAA 2023, LNCS, vol. 13946, pp. 696–700. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-30678-5_58
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