Feature-Selection Based Data Prioritization in Mobile Traffic Prediction Using Machine Learning

Yoshinobu Yamada, Ryoichi Shinkuma, Takehiro Sato, Eiji Oki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Recently, the demand for realtime and accurate prediction of mobile traffic has been growing in traffic engineering and dynamic resource allocation that work to handle increased mobile data traffic. However, most conventional prediction techniques assumed that traffic logs at every unit time at every base station are perfectly available. This assumption is critical in realtime mobile traffic prediction because the volume of traffic log data collected at base stations is huge and they compete bandwidth with normal user application traffic when they are sent from base stations to the server that performs prediction. Therefore, in realtime mobile traffic prediction, we should consider the condition in which the bandwidth ensured for forwarding traffic log data is limited. In this paper, we propose a method that prioritizes traffic log data in the basis of the contribution to prediction accuracy; each base station sends more important traffic log data to the server with higher priority. The importance of each data entry of traffic log data means how much prediction accuracy would degrade if the entry is missing. The proposed method enables us to reduce the volume of traffic log data sent from base stations to the server while maintaining prediction accuracy at the sufficient level. Our simulation study using a real dataset of mobile-traffic measurement validates our method in terms of prediction accuracy under the limitation of available traffic log data.

Original languageEnglish
Title of host publication2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538647271
DOIs
Publication statusPublished - 2018
Externally publishedYes
Event2018 IEEE Global Communications Conference, GLOBECOM 2018 - Abu Dhabi, United Arab Emirates
Duration: 2018 Dec 92018 Dec 13

Publication series

Name2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings

Conference

Conference2018 IEEE Global Communications Conference, GLOBECOM 2018
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period18/12/918/12/13

ASJC Scopus subject areas

  • Information Systems and Management
  • Renewable Energy, Sustainability and the Environment
  • Safety, Risk, Reliability and Quality
  • Signal Processing
  • Modelling and Simulation
  • Instrumentation
  • Computer Networks and Communications

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