Performance and Usage Patterns of Mobile Networks

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School of Electrical Engineering | Doctoral thesis (article-based) | Defence date: 2021-11-19
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Authors

Date

2021

Department

Tietoliikenne- ja tietoverkkotekniikan laitos
Department of Communications and Networking

Major/Subject

Mcode

Degree programme

Language

en

Pages

144 + app. 94

Series

Aalto University publication series DOCTORAL DISSERTATIONS, 150/2021

Abstract

The popularity of mobile devices and the availability of various services over mobile cellular networks has increased over the past twenty years. Over time, mobile cellular network technologies have evolved, and the performance of wireless links from mobile devices to the core networks is increasing. Mobile applications and services require differ- ent network qualities to meet users’ expectations and increase the Quality of Experience (QoE). To support the increased number of users, and to deliver the capacity required by applications, mobile networks have become complex systems. The demand for high-quality experience in mobile cellular networks is in the interest of both end-users and providers. However, mobile network performance is affected by a multitude of network features. This includes radio technology, network bandwidth and coverage, signal strength, mobility, throughput, latency, and data usage patterns of users. This thesis analyzes mobile cellular network performance and usage patterns. We apply different data analysis methods and use various datasets collected through crowdsourcing and testbeds. We study various features of mobile networks and their effect on mobile network performance. We propose an estimation method for QoE in web browsing and discuss factors affecting web-flows performance in mobile networks. We present different models based on machine learning that predict network throughput, cluster, and classify mobile users’ data usage patterns. This thesis contributes to the evolving mobile networks by studying various network features that determine the performance of mobile networks and the data usage patterns of mobile users. The large-scale crowdsourced mobile network measurement datasets provide valuable input for understanding factors affecting the performance and quality of mobile networks. The study on the data usage patterns of mobile users provides significant input for understanding mobile users’ data usage patterns and behavior across different countries. The classification model on network stability and data usage patterns can be valuable input for network resource optimization. The study conducted on the feasibility of teleoperated driving and correlation-based network feature mapping shows how crowd-sourced datasets can be used to analyze different uses cases in mobile networks.

Description

Supervising professor

Manner, Jukka, Prof., Aalto University, Department of Communications and Networking, Finland

Thesis advisor

Ott, Jörg, Prof., Aalto University, Finland

Keywords

mobile networks, data usage, performance measurement, QoE

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Parts

  • [Publication 1]: E. A. Walelgne, J. Manner, V. Bajpai and J. Ott. Analyzing Throughput and Stability in Cellular Networks. In 30th IEEE/International Federation for Information Processing (IFIP) Network Operations and Management Symposium, Taipei, Taiwan, pp. 1–9 , 2018.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201812075890
    DOI: 10.1109/NOMS.2018.8406261 View at publisher
  • [Publication 2]: E. A. Walelgne, K. Setälä, V. Bajpai, S. Neumeier, J. Manner, J. Ott. Factors Affecting Performance of Web Flows in Cellular Networks. In 17th International Federation for Information Processing (IFIP)/IEEE Networking Conference, Zurich, Switzerland, pp. 73–81, 2018.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201906033416
    DOI: 10.23919/IFIPNetworking.2018.8696661 View at publisher
  • [Publication 3]: A. S. Asrese, E. A. Walelgne, V. Bajpai, A. Lutu, Ö. Alay, J. Ott. Measuring Web Quality of Experience in Cellular Networks. In Springer Passive and Active Measurement Conference (PAM), Puerto Varas, Chile, pp. 18–33, 2019.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201905062716
    DOI: 10.1007/978-3-030-15986-3_2 View at publisher
  • [Publication 4]: E. A. Walelgne, A. S. Asrese, J. Manner, V. Bajpai, J. Ott. Understanding Mobile Data Usage Patterns and User Behavior Across Countries from the Edge. Transactions on Network and Service Management (TNSM), pp. 3798 - 3812, 2020. Vol. 18, Issue 3, Sept. 2021.
    DOI: 10.1109/TNSM.2020.3037503 View at publisher
  • DOI: 10.1016/j.comnet.2020.107737 View at publisher
  • [Publication 6]: S. Neumeier, E. A. Walelgne, V. Bajpai, J. Ott, C. Facchi. Measuring the Feasibility of Teleoperated Driving in Mobile Networks. In 2019 Network Traffic Measurement and Analysis (TMA), Paris, France, pp. 113–120, 2019.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201909035114
    DOI: 10.23919/TMA.2019.8784466 View at publisher
  • [Publication 7]: K. Apajalahti, E. A. Walelgne, J. Manner, E. Hyvönen. Correlation-Based Feature Mapping of Crowdsourced LTE Data. In 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Bologna, Italy, pp. 1–7, 2018.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201902251813
    DOI: 10.1109/PIMRC.2018.8580999 View at publisher

Citation

Permanent link to this item

https://urn.fi/URN:ISBN:978-952-64-0571-1

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[diss] Sähkötekniikan korkeakoulu / ELEC