VANETs are proved to be the adequate solution to High traffic problems. Controlling congestion will effectively reduce the delay, data loss and enhance the stability of ITS. This proposal introduces an intelligent congestion control strategy which deals with the three phases to detects and control congestion. First phase detects congestion by measuring the Channel Busy Time. In the second phase the information is collected, filtered and clustered using K-means machine learning algorithm which classifies information based on type and deadline. The third phase is to set right priorities for each cluster and send notifications to the High speed vehicle group with greater priority. The Strategy focuses on controlling congestion by sending right cluster of messages to appropriate vehicles. Results from runtime highlights that the projected strategy master existing in terms of delay, throughput and also improves the efficiency of the system.


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    Title :

    An Effective Congestion Control System for Vehicular Adhoc Networks Using Multidimensional Data Clustering


    Additional title:

    Lect. Notes on Data Eng. and Comms.Technol.


    Contributors:

    Conference:

    International Conference on Sustainable Communication Networks and Application ; 2019 ; Erode, India July 30, 2019 - July 31, 2019



    Publication date :

    2019-11-07


    Size :

    7 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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