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    An analytical framework for distributed and centralized mobility management protocols

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    Author
    Balfaqih, Mohammed
    Balfagih, Zain
    Shepelev, Vladimir
    Alharbi, Soltan
    Jabbar, Waheb
    Subject
    Distributed Mobility Management
    Proxy Mobile IPv6
    Modeling and Analysis
    Performance Evaluation
    Date
    2022-07-30
    
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    Abstract
    Proxy Mobile IPv6 (PMIPv6) maintains the mobility management of mobile users without involving them in the signaling of mobility process. The main limitations of PMIPv6 are the high latency and packet loss. Consequently, IETF has addressed these limitations by standardizing Fast Handover for Proxy Mobile IPv6 (PFMIPv6) protocols. The whole processes of PMIPv6 and PFMIPv6 protocols, including mobility management and connectivity needs, are based on a centralized and static mobility anchor. Therefore, the centralized anchor usually suffers from enormous burdens and hence degradation in performance, scalability, and reliability of the network. Lately, Distributed Mobility Management (DMM) solution is introduced based on PMPv6 to tackle the issue of relying on a single entity. Analyzing and investigating the performance of these centralized and distributed solutions depends on traffic characteristics and user mobility model. Accordingly, we propose through these two factors an analytical framework to evaluate the handover performance of PMIPv6, PFMIPv6 and DMM in vehicular environment. Our analysis and experimental validation are very significant to determine the impacts of different network parameters on the handover performance of these protocols to facilitate decision making on which analytical framework must be adopted in a network. Analytical results demonstrate that there is a trade-off between network parameters and handover performance metrics. PFMIPv6 is the most suited protocol for low to high mobility scenarios in term of handover performance.
    Department
    Computer Science
    Publisher
    Springer Berlin Heidelberg
    Journal title
    Journal of Ambient Intelligence and Humanized Computing
    DOI
    https://doi.org/10.1007/s12652-020-01749-x
    ae974a485f413a2113503eed53cd6c53
    https://doi.org/10.1007/s12652-020-01749-x
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