Creation and maintaining of the one-to-one communication link between the nodes in Vehicular Adhoc Networks are challenging. The model which is very much efficient for one particular scenario will not work at the same level of efficiency for another environment. The mobility of the nodes in the network plays a crucial role in establishing a reliable communication model in the VANETs. Analyzing the nature of mobility inside a particular network based on logical and historical data paves an efficient way in the routing of packets by predicting the best route and improve the quality of the network, reliability, and other performance in terms of serviceability. This paper aims to analyze the drawbacks of existing mobility models utilizing various network quality parameters by classifying them into microscopic and macroscopic mobility models. With the insight gained from the analysis, we propose two methodologies where the realistic model for the VANETs can be established. The models are architected with the help of the information provided by the Geographic information system. The conventional mobility models include excessive details such as road and street layouts, intersection with traffic signals, acceleration and deceleration, building, and other obstacles in a realistic mobility model, that requires prolonged time to design and optimize, it should complicate the simulation. Designing an effective, realistic mobility model is crucial. The key objectives of this proposal are to architect realistic VANETs mobility models by taking into account the real-time road environment and actual data according to the traffic demand and improving the real-time performance of VANETs.


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    Title :

    Enhancing Mobility Based on Realistic Models for Vehicular Ad Hoc Networks



    Publication date :

    2021-04-30


    Remarks:

    oai:zenodo.org:5524598
    International Journal of Engineering and Advanced Technology (IJEAT) 10(3) 220-227



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    000




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