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논문검색

In-memory Distributed Processing Method for Traffic Big Data to Analyze and Share Traffic Events in Real Time among Social Groups

초록

영어

In this paper, we propose an in-memory distributed processing method that can rapidly process vehicle location and traffic event data using Spark Streaming. The proposed system enables to share information about surrounding vehicles, pedestrians, and traffic events in real time with drivers who use the WEVING service. In the proposed method, vehicle location and traffic event streams are indexed using the grid indexing technique according to time, and the continuous range query method is processed based on the index. Also, traffic events are grouped based on occurrence time, location, content, and road segment of the traffic event transferred in real time in order to avoid duplicated traffic events. Through experiments, we show that the proposed method is able to deduplicate similar traffic events efficiently.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Proposed In-Memory Traffic Big Data Processing Technique
 4. Experiments
 5. Conclusion
 References

저자정보

  • Dojin Choi Department of Computer Engineering, Korea Transportation of National University, Chungju, Chungbuk, Republic of Korea
  • Bosung Kim Department of Information Technology Convergence, Korea Transportation of National University, Chungju, Chungbuk, Republic of Korea
  • Insu Bae Department of Information Technology Convergence, Korea Transportation of National University, Chungju, Chungbuk, Republic of Korea
  • Seokil Song Department of Computer Engineering, Korea Transportation of National University, Chungju, Chungbuk, Republic of Korea

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