부산대학교 도서관

BackgroundHigh energy physics (HEP) experiments aimed at studying elementary particles and their interactions need to acquire and analyze large amount of experimental data to discover new particles or measure the properties of known particles. With the development of HEP experiments, the energy and luminosity of accelerators are increasing, the scale of experiments is expanding, and consequently the acquisition, processing and analysis of large amount of data will be more challenging.PurposeThis study aims to design and implement a more advanced or effective distributed data acquisition framework to acquire and process the huge amount of data generated by tracking detectors for future HEP experiments where the number of channels and data volume of tracking detectors is extremely large.MethodsThe distributed data acquisition framework in HEP experiment divided into data flow software and online software was redesigned by using Hadoop big data framework, mainstream open source big data processing components was adopted to develope a new data acquisition framework—BigDataDAQ. Finally, this framework was applied to the prototype of the time projection chamber for verification.Results & ConclusionsResults of performance test show that the framework has high performance in data throughput and data processing, and can be easily deployed and managed. It provides a feasible solution for the future data acquisition system of high energy physics experiment.