This research aims to provide a traffic-aware traffic signal control framework to relieve traffic congestion due to rush-hour traffic, traffic accidents or holidays. The proposed framework incorporates a traffic signal control algorithm in Software-Defined Networking (SDN), cloud computing, and fog computing. We expect this framework can adapt to traffic conditions and then adjust the timing of traffic signals to relieve traffic flow and reduce driving time effectively. To avoid traffic congestion, we have to rely on a large number of traffic report messages and diversified traffic services in the proposed framework. Therefore, road traffic congestion may cause network traffic congestion. To manage network traffic efficiently, we proposed to use SDN to effectively and dynamically allocate bandwidth resource such that we can manage road traffic effectively. On the other hand, cloud computing and fog computing have their respective advantages in data processing. We use fog computing to not only reduce the network traffic to and from the network center node but also shorten system response time. We use cloud computing to carry computation-intensive process. Through simulations, the proposed framework is proved to be able to reduce the proportion of waiting time and increase the proportion of driving time.


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    Title :

    Traffic-Aware Traffic Signal Control Framework Based on SDN and Cloud-Fog Computing


    Contributors:


    Publication date :

    2018-08-01


    Size :

    1056024 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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