Earticle

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

키워드

저자

• 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 ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605