Packet-level Overload Estimation in LTE Networks using Passive Measurements Article Swipe
Vivek Adarsh
,
Michael Nekrasov
,
Ellen Zegura
,
Elizabeth Belding
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1145/3355369.3355574
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1145/3355369.3355574
Over 87% of US mobile wireless subscriptions are currently held by LTE-capable devices [34]. However, prior work has demonstrated that connectivity may not equate to usable service. Even in well-provisioned urban networks, unusually high usage (such as during a public event or after a natural disaster) can lead to overload that makes the LTE service difficult, if not impossible to use, even if the user is solidly within the coverage area. A typical approach to detect and quantify overload on LTE networks is to secure the cooperation of the network provider for access to internal metrics. An alternative approach is to deploy multiple mobile devices with active subscriptions to each mobile network operator (MNO). Both approaches are resource and time intensive. In this work, we propose a novel method to estimate overload in LTE networks using only passive measurements, and without requiring provider cooperation. We use this method to analyze packet-level traces for three commercial LTE service providers, T-Mobile, Verizon and AT&T, from several locations during both typical levels of usage and during public events that yield large, dense crowds. This study presents the first look at overload estimation through the analysis of unencrypted broadcast messages. We show that an upsurge in broadcast reject and cell barring messages can accurately detect an increase in network overload.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1145/3355369.3355574
- https://dl.acm.org/doi/pdf/10.1145/3355369.3355574
- OA Status
- gold
- Cited By
- 6
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2980660444
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W2980660444Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1145/3355369.3355574Digital Object Identifier
- Title
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Packet-level Overload Estimation in LTE Networks using Passive MeasurementsWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
- Publication date
-
2019-10-18Full publication date if available
- Authors
-
Vivek Adarsh, Michael Nekrasov, Ellen Zegura, Elizabeth BeldingList of authors in order
- Landing page
-
https://doi.org/10.1145/3355369.3355574Publisher landing page
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-
https://dl.acm.org/doi/pdf/10.1145/3355369.3355574Direct link to full text PDF
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YesWhether a free full text is available
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-
goldOpen access status per OpenAlex
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https://dl.acm.org/doi/pdf/10.1145/3355369.3355574Direct OA link when available
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Computer science, Computer network, Network packet, Provisioning, Cellular network, Radio access network, Service provider, Mobile computing, Service (business), Mobile station, Economics, Economy, Base stationTop concepts (fields/topics) attached by OpenAlex
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6Total citation count in OpenAlex
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2022: 1, 2021: 5Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.However, | 14 |
| abstract_inverted_index.analysis | 191 |
| abstract_inverted_index.approach | 73, 98 |
| abstract_inverted_index.coverage | 69 |
| abstract_inverted_index.estimate | 130 |
| abstract_inverted_index.increase | 212 |
| abstract_inverted_index.internal | 94 |
| abstract_inverted_index.messages | 207 |
| abstract_inverted_index.metrics. | 95 |
| abstract_inverted_index.multiple | 102 |
| abstract_inverted_index.networks | 81, 134 |
| abstract_inverted_index.operator | 112 |
| abstract_inverted_index.overload | 49, 78, 131, 187 |
| abstract_inverted_index.presents | 182 |
| abstract_inverted_index.provider | 90, 142 |
| abstract_inverted_index.quantify | 77 |
| abstract_inverted_index.resource | 117 |
| abstract_inverted_index.service. | 26 |
| abstract_inverted_index.wireless | 5 |
| abstract_inverted_index.T-Mobile, | 158 |
| abstract_inverted_index.broadcast | 194, 202 |
| abstract_inverted_index.currently | 8 |
| abstract_inverted_index.disaster) | 45 |
| abstract_inverted_index.locations | 164 |
| abstract_inverted_index.messages. | 195 |
| abstract_inverted_index.networks, | 31 |
| abstract_inverted_index.overload. | 215 |
| abstract_inverted_index.requiring | 141 |
| abstract_inverted_index.unusually | 32 |
| abstract_inverted_index.accurately | 209 |
| abstract_inverted_index.approaches | 115 |
| abstract_inverted_index.commercial | 154 |
| abstract_inverted_index.difficult, | 55 |
| abstract_inverted_index.estimation | 188 |
| abstract_inverted_index.impossible | 58 |
| abstract_inverted_index.intensive. | 120 |
| abstract_inverted_index.providers, | 157 |
| abstract_inverted_index.LTE-capable | 11 |
| abstract_inverted_index.alternative | 97 |
| abstract_inverted_index.cooperation | 86 |
| abstract_inverted_index.unencrypted | 193 |
| abstract_inverted_index.connectivity | 20 |
| abstract_inverted_index.cooperation. | 143 |
| abstract_inverted_index.demonstrated | 18 |
| abstract_inverted_index.packet-level | 150 |
| abstract_inverted_index.measurements, | 138 |
| abstract_inverted_index.subscriptions | 6, 107 |
| abstract_inverted_index.well-provisioned | 29 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.4300000071525574 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.80085043 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |