research-article

Multiway Reliability Analysis of Mobile Broadband Networks

Authors:

Ahmed ElmokashfiAuthors Info & Claims

IMC '19: Proceedings of the Internet Measurement Conference

Pages 358 - 364

https://doi.org/10.1145/3355369.3355591

Published: 21 October 2019 Publication History

Abstract

Understanding and characterizing the reliability of a mobile broadband network is a challenging task due to the presence of a multitude of root causes that operate at different temporal and spatial scales. This, in turn, limits the use of classical statistical methods for characterizing the mobile network's reliability. We propose leveraging tensor factorizations, a well-established data mining method, to address this challenge. We represent a year-long time series of outages, from two mobile operators as multi-way arrays, and demonstrate how tensor factorizations help in extracting the outage patterns at various time-scales, making it easy to locate possible root causes. Unlike traditional methods of time series analysis, tensor factorizations provide a compact and interpretable picture of outages.

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Cited By

Fida MRoald MAcar EElmokashfi A(2023)Modeling Variation in Mobile Download Speed in Presence of Missing SamplesIEEE Transactions on Mobile Computing10.1109/TMC.2022.3231928(1-16)Online publication date: 2023
https://doi.org/10.1109/TMC.2022.3231928
Shen SFeng YXu MZhang CWang XWang WLeung V(2023)A Holistic QoS View of Crowdsourced Edge Cloud Platform2023 IEEE/ACM 31st International Symposium on Quality of Service (IWQoS)10.1109/IWQoS57198.2023.10188726(01-10)Online publication date: 19-Jun-2023
https://doi.org/10.1109/IWQoS57198.2023.10188726
Feng YShen SXu MZhang CWang XWang XWang WLeung V(2023)A large-scale holistic measurement of crowdsourced edge cloud platformWorld Wide Web10.1007/s11280-023-01201-y26:5(3561-3584)Online publication date: 5-Aug-2023
https://doi.org/10.1007/s11280-023-01201-y
Show More Cited By

Index Terms

Multiway Reliability Analysis of Mobile Broadband Networks
1. Networks
  1. Network performance evaluation
    1. Network performance analysis
  2. Network properties
    1. Network reliability

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cover image ACM Conferences

IMC '19: Proceedings of the Internet Measurement Conference

October 2019

497 pages

ISBN:9781450369480

DOI:10.1145/3355369

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 21 October 2019

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The Research Council of Norway

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IMC '19

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IMC '19: ACM Internet Measurement Conference

October 21 - 23, 2019

Amsterdam, Netherlands

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IMC '19 Paper Acceptance Rate 39 of 197 submissions, 20%;

Overall Acceptance Rate 277 of 1,083 submissions, 26%

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Cited By

Fida MRoald MAcar EElmokashfi A(2023)Modeling Variation in Mobile Download Speed in Presence of Missing SamplesIEEE Transactions on Mobile Computing10.1109/TMC.2022.3231928(1-16)Online publication date: 2023
https://doi.org/10.1109/TMC.2022.3231928
Shen SFeng YXu MZhang CWang XWang WLeung V(2023)A Holistic QoS View of Crowdsourced Edge Cloud Platform2023 IEEE/ACM 31st International Symposium on Quality of Service (IWQoS)10.1109/IWQoS57198.2023.10188726(01-10)Online publication date: 19-Jun-2023
https://doi.org/10.1109/IWQoS57198.2023.10188726
Feng YShen SXu MZhang CWang XWang XWang WLeung V(2023)A large-scale holistic measurement of crowdsourced edge cloud platformWorld Wide Web10.1007/s11280-023-01201-y26:5(3561-3584)Online publication date: 5-Aug-2023
https://doi.org/10.1007/s11280-023-01201-y
Grassi GTeixeira RBarakat CCrovella M(2021)Leveraging Website Popularity Differences to Identify Performance AnomaliesIEEE INFOCOM 2021 - IEEE Conference on Computer Communications10.1109/INFOCOM42981.2021.9488832(1-10)Online publication date: 10-May-2021
https://doi.org/10.1109/INFOCOM42981.2021.9488832

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