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

    5 Citations (Scopus)
    26 Downloads (Pure)

    Abstract

    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
    PublisherIEEE
    Pages78-80
    Number of pages3
    ISBN (Print)978-1-4673-9501-4
    DOIs
    Publication statusPublished - 5 Oct 2015

    Publication series

    Name
    PublisherIEEE

    Keywords

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

    Cite this

    Zhao, Z., Karimzadeh Motallebi Azar, M., Braun, T., Pras, A., & van den Berg, H. L. (2015). A Demonstration of Mobility Prediction as a Service in Cloudified LTE Networks. In Proceedings of the 4th International Conference on Cloud Networking, CloudNet 2015 (pp. 78-80). Danvers, MA, USA: IEEE. https://doi.org/10.1109/CloudNet.2015.7335285