A hybrid IoT traffic generator for mobile network performance assessment

Wei Hung Hsu, Qiuhui Li, Xue Hai Han, Chih Wei Huang

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

8 Scopus citations

Abstract

Internet of Things (IoT) technology is the key enabler of the future with a massive number of connected devices. With the evolution of Machine Type Communications (MTC), the number of MTC devices in mobile networks is increasing rapidly to support IoT services. The massive number of short and bursty sessions introduced by MTC devices may result in congestion and system overload impacting human to human (H2H) communications in mobile networks. To study the overall network performance for the future scenarios to come, a flexible traffic model based on practical data is necessary. Unfortunately, scalable and realistic MTC traffic data is inaccessible in most cases. In this work, we propose a hybrid traffic framework by integrating open big data and MTC traffic models. The generated MTC traffic is based on geo-referenced H2H activities and can be used to help assessing mobile network performance.

Original languageEnglish
Title of host publication2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages441-445
Number of pages5
ISBN (Electronic)9781509043729
DOIs
StatePublished - 19 Jul 2017
Event13th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2017 - Valencia, Spain
Duration: 26 Jun 201730 Jun 2017

Publication series

Name2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017

Conference

Conference13th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2017
Country/TerritorySpain
CityValencia
Period26/06/1730/06/17

Keywords

  • IoT
  • LTE mobile network
  • MTC
  • Traffic generator

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