Modeling Variation in Mobile Download Speed in Presence of Missing Samples

Mah Rukh, Fida ORCID: 0000-0001-7660-1150, Roald, Marie ORCID: 0000-0002-9571-8829, Acar, Evrim ORCID: 0000-0002-3737-292X and Elmokashfi, Ahmen ORCID: 0000-0001-9964-214X (2024) Modeling Variation in Mobile Download Speed in Presence of Missing Samples. IEEE TRANSACTIONS ON MOBILE COMPUTING, 23 (2). 1200 -1214. doi:10.1109/TMC.2022.3231928

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13915 Mah-Rukh Fida et al (2024) Modelling Variation in Mobile Download Speed - Accepted version.pdf - Accepted Version
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Abstract

A stably fast mobile broadband connectivity is key to customer retention. Mobile networks, however, suffer unpredictability in performance. Analyzing variability in network speed is, therefore, challenging since it tends to exhibit patterns at several time scales. Additionally, frequently monitoring it over time, is costly. In this article, we analyze speed measurements from 78 stationary probes, spread across Norway. Monitoring was performed thrice per day across the year, to assess performance of the two largest network operators. Despite being unique, the dataset involves a non-trivial extent of missing data. This study investigates the effect of missing data on the extracted performance patterns. We capture patterns with tensor factorizations, that show that missing data at random has a minimal effect on the identified patterns, and that depending upon the determinism of an operator’s performance, the acceptable size and structure of missing data varies. Our analysis shows that, for a probe, the difference in speed variation between real and imputed speed values can be around 7% for up to 40% missing data. We also identify that congestion, routine maintenance and sub-optimal network configuration cause high speed variability. These findings can help operators improving their offerings and deciding on optimal performance monitoring frequency.

Item Type: Article
Article Type: Article
Additional Information: Full published version is available to current University of Gloucestershire students and staff via the IEEE database, see publisher link below.
Uncontrolled Keywords: Probes; Tensors; Handover; Broadband communication; Velocity measurement; Metadata; Frequency measurement; Download speed; Speed variation; Tensor factorizations; Imputation; Missing data
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Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas: Applied Business & Technology
Depositing User: Mah Rukh
Date Deposited: 17 Apr 2024 14:27
Last Modified: 26 Apr 2024 13:58
URI: https://eprints.glos.ac.uk/id/eprint/13915

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