We have constructed a wide-field photometric survey system called as the Korea Microlensing Telescope Network (KMTNet) in 2015. It consists of three 1.6 m optical telescopes equipped with mosaic CCD cameras. Four 9k CCDs were installed on the focal plane of each telescope. In this paper, we present the crosstalk analysis of the KMTNet mosaic CCD images. The crosstalk victims caused by bright sources were visible at eight sub-images obtained through different readout ports of each CCD. The crosstalk coefficients were estimated to be several tens of 10-4 in maximum, differing from sub-image to sub-image, and the non-linearity effect certainly appeared at the victims made from saturated sources. We developed software functions to correct the crosstalk effect of the KMTNet CCD images. The software functions showed satisfying results to remove clearly most of the crosstalk victims and have been implemented in the KMTNet image processing pipeline since 2015 September.

We develop a real-time data transfer system for the Korea Microlensing Telescope Network (KMTNet) photometry data and test whether it is suitable for Korea Astronomy and Space Science Institute (KASI) and three different observatories, which are Cerro Tololo Inter-Ameriacan Observatory (CTIO) in Chile, Siding Springs Observatory (SSO) in Australia, and South African Astronomical Observatory (SAAO) in South Africa. For this test, we use a high speed global network being dedicated for researches. From the test, we obtain that the elapsed times between KASI and each three observatories, CTIO, SSO, and SAAO to transfer 650 MB of data are 99.0, 9.2, 119.0 seconds, respectively. This means that the system can be used for the real-time data processing of KMTNet.

Real-time data reduction pipeline for the Korea Microlensing Telescope Network (KMTNet) was developed by Korea Astronomy and Space Science Institute (KASI). The main goal of the data reduction pipeline is to find variable objects and to record their light variation from the large amount of observation data of about 200 GB per night per site. To achieve the goal we adopt three strategic implementations: precision pointing of telescope using the cross correlation correction for target fields, realtime data transferring using kernel-level file handling and high speed network, and segment data processing architecture using the Sun-Grid engine. We tested performance of the pipeline using simulated data which represent the similar circumstance to CTIO (Cerro Tololo Inter-American Observatory), and we have found that it takes about eight hours for whole processing of one-night data. Therefore we conclude that the pipeline works without problem in real-time if the network speed is high enough, e.g., as high as in CTIO.

We constructed two test server systems for KMTNet data management. One is the photometry database server which is optimized for stable operation, and the other is the photometric data process server which is optimized for fast I/O between devices. The performances of servers and data storage units were tested using various methods. Database upload was also checked using five different methods. From tests, we concluded that the most efficient method to upload photometric data processing results to database is the use of three nodes with job scheduler under the InnoDB engine. In this study we provide the test results for prototype servers for KMTNet data management.

We constructed a photometric database system which is optimally designed for microlensing events from KMTNet (Korea Microlensing Telescope Network) observation. We developed a framework software for the convenience of archiving, uploading, searching, and downloading of processed photometric data. From various tests for optimal data archiving engines, we found that the MyISAM storage engine shows the best performance. For the high performance of database system, data types of each field are carefully suggested from various combinations of tests especially to correct round-off errors. The developed framework provides the convenience of access to the database server using query forms via web pages, and displays the light curve of selected target for a quick view.

We have designed data processing server system to include data archiving, photometric processing and light curve analysis for KMTNet (Korea Microlensing Telescope Network). Outputs of each process are reported to the main photometric database, which manages the whole processing steps and archives the photometric results. The database is developed using ORACLE 11g Release 2 engine. It allows to select objects applying any set of criteria such as RA/DEC coordinate and Star ID, etc. We tested the performance of the database using the OGLE photometric data. The searching time for querying 70,000,000 records was under 1 second. The database is fully accessed using query forms via web page.