A Demonstration of Mobility Prediction as a Service in Cloudified LTE Networks

Zhongliang Zhao, Morteza Karimzadeh Motallebi Azar, Torsten Braun, Aiko Pras, Hans Leo van den Berg

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    6 Citations (Scopus)
    52 Downloads (Pure)


    Location prediction has attracted a significant amount of research effort. Being able to predict users’ movement benefits a wide range of communication systems, including location-based service/applications, mobile access control, mobile QoS provision, and resource management for mobile computation and storage management. In this demo, we present MOBaaS, which is a cloudified Mobility and Bandwidth prediction services that can be instantiated, deployed, and disposed on-demand. Mobility prediction of MOBaaS provides location predictions of a single/group user equipments (UEs) in a future moment. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operations. We demonstrate an example of real-time mobility prediction service deployment running on OpenStack platform, and the potential benefits it bring to other invoking services.
    Original languageUndefined
    Title of host publicationProceedings of the 4th International Conference on Cloud Networking, CloudNet 2015
    Place of PublicationDanvers, MA, USA
    Number of pages3
    ISBN (Print)978-1-4673-9501-4
    Publication statusPublished - 5 Oct 2015
    Event4th International Conference on Cloud Networking, CloudNet 2015 - Niagara Falls, ON, Canada
    Duration: 5 Oct 20157 Oct 2015

    Publication series



    Conference4th International Conference on Cloud Networking, CloudNet 2015
    Other5-7 October 2015


    • EWI-26341
    • IR-98281
    • METIS-314980

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