Mr. Yunlin Tu Profile

Yunlin Tu

at UESTC

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Proceedings Article | 15 December 2022 Paper

A cost-effective real-time distributed computing platform with apache spark structured streaming for DAS

Yunlin Tu, Yuwen Sun, Lishuang Yao, Huijuan Wu

Proceedings Volume 12478, 124781W (2022) https://doi.org/10.1117/12.2654611

KEYWORDS: Distributed computing, Data processing, Fiber optics sensors, Fiber optics, Sensors

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Fiber-optical distributed acoustic sensor (DAS) based on the phase-sensitive optical time-domain reflectometry (Φ- OTDR), provides a highly dense and cost-effective continuous sensing network for our environment safefy monitoring in a wide range by using the existed or buried communication cable as its sensing media. However, the continuous huge spatial-temporal data stream generated by long-distance Fiber-optic Distributed Acoustic Sensor (DAS) poses a great challenge to the single central processing unit (CPU) or graphical processing unit (GPU) machine with traditional centralized processing style. Thus, a distributed computing platform is built in this paper based on Apache Spark Structured Streaming, which provides a cost-effective solution with relatively high throughput and high real time capability. The throughput is improved by 75% and latency reduces by 19.71% in virtual-machine test, while the throughput is improved by 44% and the latency reduces by 37.53% on average in an optimal four-node cluster compared to a single node in real-machine test. It provides a promising real-time distributed computing scheme for DAS especially with large or super large sensing arrays in a large range or a highly dense time-space acquisition network.

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