Abstract
Since the twenty-first century, traffic big data has gained unprecedented attention as the basis of many intelligent transportation solutions. Cloud platform technology and big data mining technology have changed the restrictions of traditional traffic management administrative areas, established a comprehensive and three-dimensional intelligent transportation system, and provided new technologies and new means for traffic supervision, security early warning, and high-efficiency management and control. This paper analyzes the importance of the combination of intelligent traffic data analysis center and traffic big data and cloud platform technology from the technical and functional levels, and proposes the architecture design and implementation of the cloud big data platform based on cloud computing.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Park, Kyounghyun, M.C. Nguyen, and H. Won. 2015. Web-based collaborative big data analytics on big data as a service platform. International Conference on Advanced Communication Technology.
Sfrent, Andrei, and F. Pop. 2015. Asymptotic scheduling for many task computing in Big Data platforms. Information Sciences 319: 71–91.
Elagib, Sara B., A.H.A. Hashim, and R.F. Olanrewaju. 2017. A proposed architecture for generic and scalable CDR analytics platform utilizing big data technology. Advanced Science Letters 23 (11): 11149–11152.
Jian, Fu, J. Sun, and K. Wang. 2017. SPARK—A big data processing platform for machine learning. International Conference on Industrial Informatics-Computing Technology.
Singhal, Ayush, R. Pant, and P. Sinha. 2018. “AlertMix: A Big Data platform for multi-source streaming data.”
Abouzeid, Azza, et al. 2009. HadoopDB: An architectural hybrid of MapReduce and DBMS technologies for analytical workloads. Proceedings of the Vldb Endowment 2.1: 922–933.
Qi, Shi, and M. Abdel-Aty. 2015. Big Data applications in real-time traffic operation and safety monitoring and improvement on urban expressways. Transportation Research Part C 58: 380–394.
Baccarelli, Enzo, et al. 2016. Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing: review, challenges, and a case study. Computers & Chemical Engineering 91 (2): 182–194.
Cárdenasbenítez, Néstor, et al. 2016. Traffic congestion detection system through connected vehicles and big data. Sensors 16 (5): 599.
Buyya, Rajkumar, et al. 2009. Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation Computer Systems 25 (6): 599–616.
Zhen, Xie, et al. 2017. Modeling traffic of big data platform for large scale datacenter networks. IEEE International Conference on Parallel & Distributed Systems (in Chinese).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Gu, Y., Fu, L. (2020). How to Build Hadoop in the Field of Transportation by Cloud Computing. In: Huang, C., Chan, YW., Yen, N. (eds) Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019). Advances in Intelligent Systems and Computing, vol 1088. Springer, Singapore. https://doi.org/10.1007/978-981-15-1468-5_29
Download citation
DOI: https://doi.org/10.1007/978-981-15-1468-5_29
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-1467-8
Online ISBN: 978-981-15-1468-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)