WU Qiong, HE Fanfan, FAN Xiumei. The Intelligent Control System of Traffic Light Based on Fog Computing[J]. Chinese Journal of Electronics, 2018, 27(6): 1265-1270. doi: 10.1049/cje.2018.09.015
Citation: WU Qiong, HE Fanfan, FAN Xiumei. The Intelligent Control System of Traffic Light Based on Fog Computing[J]. Chinese Journal of Electronics, 2018, 27(6): 1265-1270. doi: 10.1049/cje.2018.09.015

The Intelligent Control System of Traffic Light Based on Fog Computing

doi: 10.1049/cje.2018.09.015
Funds:  This work is supported by Shaanxi Province Hundred Talents Program, the Key Research and Development Plan of Shaanxi Province (No.2017ZDCXL-GY-05-01) and National Natural Science Foundation of China (No.61272509).
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  • Corresponding author: FAN Xiumei (corresponding author) received the B.E. degree from Tianjin University and received the Ph.D. degree in communication and control engineering from Beijing Jiaotong University, China. She is a professor of Xi'an University of Technology and Shaanxi Province Hundred Talents Program. She has also (co-) authored more than 90 technical papers. Her research interests includes vehicular networks, fog computing, and various aspects of broadband wireless networks. (Email:xmfan@xaut.edu.cn)
  • Received Date: 2017-11-20
  • Rev Recd Date: 2018-05-25
  • Publish Date: 2018-11-10
  • The continuous increase of city motors with the improvement of society has introduced extraordinary demanding situations for the traffic situation of the town. Intelligent traffic has proposed a diversity of solutions to relieve urban traffic accidents and congestion and other troubles. It cannot regulate the cycle of traffic light in real time in keeping with the occurring traffic flux which additionally, may produce the traffic jam to result in the increase for the range of automobiles and the longer of passage time. In purpose to surmount the shortcomings of traditional traffic light control, this paper is presenting a form of intelligent control system for traffic light founding on fog computing. It calculates and shares the traffic flux situation at the intersection and the surrounding intersection through fog computing platform. Regarding the traffic flow at the intersection and the traffic flow at the surrounding intersection as the parameters, the intelligent control algorithm of traffic light is designed for achieving mutual coordination and mutual influence between different intersections, so that the traffic efficiency of each intersection is improved and the traffic flow of the entire transport network is alleviated. The simulation results showed this intelligent control system progress the traffic efficiency of every intersection and relieve the traffic flow of the whole transport network.
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  • Cisco Global Cloud Index: Forecast and Methdology 2013-2018 white Paper.
    Zhi Li, Yan Liu, Hongsong Zhu, et al., “Contact Duration Aware Cellular Traffic Offloading Over Delay Tolerant Networks”, IEEE Transactions on Vehicular Technology, Vol.64, No.2015.
    Mell P and Grance T, “The NIST definition of cloud computing”, NIST special publication, Vol.800, No.145, pp.7, 2011.
    Subashini and Kavitha V, “A survey on security issues in service delivery models of cloud computing”, Journal of Network and Computer Applications, Vol.34, No.1, pp.1-11, 2011.
    Dinh H T, Lee C, Niyato D, et al., “A survey of mobile cloud computing: Architecture, applications, and approaches”, Wireless communications and mobile computing, Vol.13, No.17, pp.1587-1611, 2013.
    Bonomi F, Milito R, Zhu J, et al., “Fog computing and its role in the Internet of Things”, Proceedings of the 1st ACM Mobile cloud Computing Workshop, Helsinki, Finland, pp.13-16, 2012.
    Yang G and Tan C H, “Certificateless public key encryption:A new generic construction and two pairing-free schemes”, Theoretical Computer Science,Vol.41, No.8, pp.127-128, 2011.
    Teng J, Wu C, “A provable authenticated certificateless group key agreement with constant rounds”, Journal of Communications & Networks, Vol.14, No.1, pp.104-110, 2012.
    Ercolani G, “Cloud computing services potential analysis: An integrated model for evaluating Software as a Service”, Cloud Computing, Vol.24, No.3, pp.77-80, 2013.
    Majid Hajibaba, Saeid Gorgin, “A review on modern distributed computing paradigms cloud computing jungle computing and fog computing”, Acm SIGCOMM Computer Communication Review, Vol.4, No.5, pp.13-15, 2012.
    Jianbing Ni, Kuan Zhang, Xiaodong Lin, et al., “Securing fog computing for internet of things applications: Challenges and solutions”, IEEE Communications Surveys & Tutorials, pp.1, 2017.
    Sripriya Srikant Adhatarao, Mayutan Arumaithurai, et al., “A fog computing based gateway to integrate sensor networks to internet”, 201729th International Teletraffic Congress (ITC 29), pp.42-47, 2017.
    Luca Cerina, Sara Notargiacomo, Matteo GrecoLuca Paccanit, et al., “A fog-computing architecture for preventive healthcare and assisted living in smart ambients”, 2017 IEEE 3rd International Forum on Research and Technologies for Society and Industry (RTSI), pp.1-6, 2017.
    Mithun Mukherjee, Rakesh Matam, Lei Shu, et al., “Security and privacy in fog computing: Challenges”, IEEE Access, pp.19293-19304, 2017.
    Yong Xiao, and Marwan Krunz, “QoE and power efficiency tradeoff for fog computing networks with fog node cooperation”, IEEE INFOCOM 2017-IEEE Conference on Computer Communications, pp.1-9, 2017.
    Zhang Y, Ren J, Liu J, et al., “A survey on emerging computing paradigms for big data”, Chinese Journal of Electronics, Vol.26, No.1, pp.1-12, 2017.
    Lina Ni, Jinquan Zhang, Changjun Jiang, et al., “Resource allocation strategy in fog computing based on priced timed petri nets”, IEEE Internet of Things Journal, pp.1216-1228, 2017.
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