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arXiv · 1612.07572

Low-cost high performance distributed data storage for multi-channel observations

Ying-bo Liu·Feng Wang·Hui Deng·Kai-fan Ji·Wei Dai·Shou-lin Wei·Bo Liang·Xiao-li Zhang
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Abstract

The New Vacuum Solar Telescope (NVST) is a 1-m solar telescope that aims to observe the fine structures in both the photosphere and the chromosphere of the Sun. The observational data acquired simultaneously from one channel for the chromosphere and two channels for the photosphere bring great challenges to the data storage of NVST. The multi-channel instruments of NVST, including scientific cameras and multi-band spectrometers, generate at least 3 terabytes data per day and require high access performance while storing massive short-exposure images. It is worth studying and implementing a storage system for NVST which would balance the data availability, access performance and the cost of development. In this paper, we build a distributed data storage system (DDSS) for NVST and then deeply evaluate the availability of real-time data storage on a distributed computing environment. The experimental results show that two factors, i.e., the number of concurrent read/write and the file size, are critically important for improving the performance of data access on a distributed environment. Referring to these two factors, three strategies for storing FITS files are presented and implemented to ensure the access performance of the DDSS under conditions of multi-host write and read simultaneously. The real applications of the DDSS proves that the system is capable of meeting the requirements of NVST real-time high performance observational data storage. Our study on the DDSS is the first attempt for modern astronomical telescope systems to store real-time observational data on a low-cost distributed system. The research results and corresponding techniques of the DDSS provide a new option for designing real-time massive astronomical data storage system and will be a reference for future astronomical data storage.

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Ying-bo Liu, Feng Wang, Hui Deng, Kai-fan Ji, Wei Dai, Shou-lin Wei, Bo Liang, Xiao-li Zhang. 2016-12-22. Low-cost high performance distributed data storage for multi-channel observations. https://arxiv.org/abs/1612.07572

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