The massive stream of data generated from traffic sensors in smart cities are huge to be handled by ordinary tools and algorithms and they take too much time for transmission to the cloud for analyzing and back again to the Internet of Things environment; those are serious issues that should be taken into consideration. Fog computing is an extension of cloud computing and it helps in solving big data transmission issues. Massive Online Analysis is a software framework used as a mining tool for big data streams. This paper proposed a Smart Routing Model that combines an existing framework called Smart Traffic for Congestion Avoidance and a new framework called Massive Online Analysis‐Fogged Routing. This framework overcomes some issues with Smart Traffic for Congestion Avoidance‐related Big Data transmission to the cloud that is solved by fog, and Big Data mining issues that are solved by using. The proposed framework implemented into three levels using three different types of simulators those are Cloudsim, Fog, and MOA simulator. The results show that using more than one virtual machine gives better performance.


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    Title :

    Simulating a Smart Car Routing Model (Implementing MFR Framework) in Smart Cities


    Contributors:


    Publication date :

    2021-04-22


    Size :

    20 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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