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A Study on Improvement of Collected Data Performance in Real-time Railway Safety Supervisory Platform

실시간 철도안전관제 플랫폼에서의 수집 데이터 성능 개선 방안 연구

  • Received : 2018.05.25
  • Accepted : 2018.11.29
  • Published : 2018.12.30

Abstract

Recently, integrated railway safety monitoring and control system, which is a convergence system based on data distribution service for railway safety monitoring and control, is under development. It collects safety data of vehicle, signal, power and safety monitoring facilities in real time and adopts communication middleware based on distributed service for mass data processing. However, in the case of a server device used as an existing control server, the performance of the distributed service middleware can not be exhibited due to low hardware performance due to safety reasons. In the safety control system, 200,000 packets per second were set as the transmission target, but the performance test of the LAB was not satisfied. In this paper, we analyze the characteristics of railway data to improve the data collection performance of existing equipment and apply DDS-based streaming transmission method to the data model of signal facilities and vehicle facilities with large packet amount according to the analysis result. As a result, it was confirmed that the throughput was improved about 30.4 times when the hardware performance was the same. We plan to improve the data processing performance by applying it to real-time railway safety integrated monitoring and control system in the future.

최근 철도안전 감시 및 제어를 위한 데이터 분산 서비스 기반의 융합시스템인 실시간 철도안전 통합 감시 제어 시스템 개발 연구가 진행되고 있다. 차량, 신호, 전력 및 안전감시 설비의 안전 데이터를 실시간 수집하고, 대용량 데이터 처리를 위하여 분산 서비스 기반의 통신 미들웨어를 채택하였다. 그러나, 기존 관제 서버로 활용되는 서버장치의 경우 안전성 등의 사유로 하드웨어 성능이 낮아 분산 서비스 미들웨어의 최대 성능을 발휘하지 못하는 실정이다. 안전관제 시스템에서도 초당 20만 패킷을 전송량 목표로 설정하였으나 LAB 기반 성능시험을 수행한 결과 충족하지 못하였다. 본 논문에서는 기존 장비의 데이터 수집 성능을 개선하고자 철도 데이터의 특성을 분석하였고, 분석 결과에 따라 패킷량이 많은 신호설비와 차량설비의 데이터 모델에 DDS 기반의 스트리밍 전송방식을 적용하였다. 그 결과 하드웨어 성능이 동일한 경우 처리량이 기존보다 약 30.4배 향상됨을 확인하였다. 향후 실시간 철도안전 통합 감시 제어 시스템에 실제로 적용하여 데이터 처리의 성능을 개선해나갈 예정이다.

Keywords

Acknowledgement

Supported by : 국토교통부

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