A Stable Clustering Architecture for Efficient Routing and Resource Allocation in Vehicular Ad Hoc Networks

UIU Institutional Repository

    • Login
    View Item 
    •   UIU DSpace Home
    • School of Science and Engineering (SoSE)
    • Department of Computer Science and Engineering (CSE)
    • M.Sc Thesis/Project
    • View Item
    •   UIU DSpace Home
    • School of Science and Engineering (SoSE)
    • Department of Computer Science and Engineering (CSE)
    • M.Sc Thesis/Project
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    A Stable Clustering Architecture for Efficient Routing and Resource Allocation in Vehicular Ad Hoc Networks

    Thumbnail
    View/Open
    012193036_MousumiAhmedMimi_finalReport-5-Apr-2022.pdf (1.830Mb)
    Date
    2022-04-05
    Author
    Mimi, Mousumi Ahmed
    Metadata
    Show full item record
    Abstract
    Vehicular Ad hoc Network (VANET) is an area of wireless networks, which makes connections among vehicles to enable vehicle to vehicle or vehicle to infrastructure communication and supports diversified applications related to road safety, data transfer, offloading resources etc. Although significant efforts have been made since the last few decades, there are still a huge number of research problems to be solved in VANET. Link stability is one of them. To make link stable, many researchers have applied single-hop and multi-hop clustering approaches to make links stable to increase connectivity time. In this work, we have used the idea of a multi-hop clustering that makes links more stable. We have applied the idea of forwarding node that connects one cluster to other clusters through cluster head resulting higher link stability. We have also extended our work to utilize the developed cluster architecture for resource allocation, which is another important area of research for vehicular applications. We applied the idea of multi-hop clustering with the forwarding node to make the link stable and minimize the time for allocating the resource and minimize the time to calculate when a node moves from one cluster to another cluster. Extended simulation has been done using SUMO and NS3 to compare the proposed clustering algorithm with other similar approaches in the literature. The results show the efficacy of our proposed algorithm in terms of different performance parameters.
    URI
    http://dspace.uiu.ac.bd/handle/52243/2407
    Collections
    • M.Sc Thesis/Project [126]

    Copyright 2003-2017 United International University
    Contact Us | Send Feedback
    Developed by UIU CITS
     

     

    Browse

    All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Copyright 2003-2017 United International University
    Contact Us | Send Feedback
    Developed by UIU CITS