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Examining cellular access systems on trains: Measurements and change detection
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DIstributed systems and communication (DISCO))ORCID iD: 0000-0003-3461-7079
(DIstributed systems and communication (DISCO))ORCID iD: 0000-0003-0368-9221
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DIstributed systems and communication (DISCO))ORCID iD: 0000-0001-7311-9334
2017 (English)In: Proceedings of the 1st Network Traffic Measurement and Analysis Conference, New York: IEEE, 2017, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

Abstract:Access to reliable high-quality communication services on trains is important for today's mobile users. Train-mounted aggregation routers that provide WiFi access to train passengers and bundle external communication over multiple cellular modems/links is an efficient way of providing such services. Still, the characteristics of such systems have received limited attention in the literature. In this paper we examine the communication characteristics of such systems based on a large data set gathered over six months from an operational Swedish railway system. We characterize the conditions in terms of usage load, train velocity profiles, and observed throughput and delay as well as the relation between these parameters. Furthermore, we examine the data from an anomaly detection perspective. Based on a changepoint detection method, we examine how the collected metrics varies over the six months. Being able to detect shifts in the metrics over time can help detect anomalous changes in the hardware or environment, and also further helps explain the factors affecting the observed behaviors.

Place, publisher, year, edition, pages
New York: IEEE, 2017. p. 1-6
Keywords [en]
cellular radio, mobile radio, railway communication, railways, wireless LAN
National Category
Computer Sciences Telecommunications
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-64541DOI: 10.23919/TMA.2017.8002916ISBN: 978-3-901882-95-1 (electronic)OAI: oai:DiVA.org:kau-64541DiVA, id: diva2:1149525
Conference
Network Traffic Measurement and Analysis Conference (TMA), 21-23 June, 2017. Dublin, Ireland
Projects
HITS
Funder
Knowledge Foundation, 4707Available from: 2017-10-16 Created: 2017-10-16 Last updated: 2018-08-14Bibliographically approved

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Garcia, JohanAlfredsson, StefanBrunström, Anna
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • vancouver
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More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NB
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  • Other locale
More languages
Output format
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