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A demonstration of mobility prediction as a service in cloudified LTE networks

  • Zhongliang Zhao
  • , Morteza Karimzadeh
  • , Torsten Braun
  • , Aiko Pras
  • , Hans Van Den Berg

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

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 languageEnglish
Title of host publication2015 IEEE 4th International Conference on Cloud Networking, CloudNet 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages78-80
Number of pages3
ISBN (Electronic)9781467395014
DOIs
StatePublished - 20 Nov 2015
Externally publishedYes
Event4th IEEE International Conference on Cloud Networking, CloudNet 2015 - Falls, Canada
Duration: 5 Oct 20157 Oct 2015

Publication series

Name2015 IEEE 4th International Conference on Cloud Networking, CloudNet 2015

Conference

Conference4th IEEE International Conference on Cloud Networking, CloudNet 2015
Country/TerritoryCanada
CityFalls
Period5/10/157/10/15

Keywords

  • Cloudification
  • LTE Networks
  • Mobile Cloud Networking
  • Mobility Prediction

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