Assessing the implications of cellular network performance on mobile content access

Research output: Contribution to journalJournal articleResearchpeer-review

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Assessing the implications of cellular network performance on mobile content access. / Kaup, Fabian; Michelinakis, Foivos; Bui, Nicola; Widmer, Joerg; Wac, Katarzyna; Hausheer, David.

In: IEEE Transactions on Network and Service Management, Vol. 13, No. 2, 2016, p. 168-180.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Kaup, F, Michelinakis, F, Bui, N, Widmer, J, Wac, K & Hausheer, D 2016, 'Assessing the implications of cellular network performance on mobile content access', IEEE Transactions on Network and Service Management, vol. 13, no. 2, pp. 168-180. https://doi.org/10.1109/TNSM.2016.2544402

APA

Kaup, F., Michelinakis, F., Bui, N., Widmer, J., Wac, K., & Hausheer, D. (2016). Assessing the implications of cellular network performance on mobile content access. IEEE Transactions on Network and Service Management, 13(2), 168-180. https://doi.org/10.1109/TNSM.2016.2544402

Vancouver

Kaup F, Michelinakis F, Bui N, Widmer J, Wac K, Hausheer D. Assessing the implications of cellular network performance on mobile content access. IEEE Transactions on Network and Service Management. 2016;13(2):168-180. https://doi.org/10.1109/TNSM.2016.2544402

Author

Kaup, Fabian ; Michelinakis, Foivos ; Bui, Nicola ; Widmer, Joerg ; Wac, Katarzyna ; Hausheer, David. / Assessing the implications of cellular network performance on mobile content access. In: IEEE Transactions on Network and Service Management. 2016 ; Vol. 13, No. 2. pp. 168-180.

Bibtex

@article{813069b6d0fc417e8517316b381ea909,
title = "Assessing the implications of cellular network performance on mobile content access",
abstract = "Mobile applications such as VoIP, (live) gaming, or video streaming have diverse QoS requirements ranging from low delay to high throughput. The optimization of the network quality experienced by end-users requires detailed knowledge of the expected network performance. Also, the achieved service quality is affected by a number of factors, including network operator and available technologies. However, most studies measuring the cellular network do not consider the performance implications of network configuration and management. To this end, this paper reports about an extensive data set of cellular network measurements, focused on analyzing root causes of mobile network performance variability. Measurements conducted on a 4G cellular network in Germany show that management and configuration decisions have a substantial impact on the performance. Specifically, it is observed that the association of mobile devices to a point of presence (PoP) within the operator's network can influence the end-to-end performance by a large extent. Given the collected data, a model predicting the PoP assignment and its resulting RTT leveraging Markov chain and machine learning approaches is developed. RTT increases of 58% to 73% compared to the optimum performance are observed in more than 57% of the measurements. Measurements of the response and page load times of popular websites lead to similar results, namely, a median increase of 40% between the worst and the best performing PoP.",
keywords = "4G mobile communication, Cellular networks, Network measurement, Performance analysis",
author = "Fabian Kaup and Foivos Michelinakis and Nicola Bui and Joerg Widmer and Katarzyna Wac and David Hausheer",
year = "2016",
doi = "10.1109/TNSM.2016.2544402",
language = "English",
volume = "13",
pages = "168--180",
journal = "IEEE Transactions on Network and Service Management",
issn = "1932-4537",
publisher = "Institute of Electrical and Electronics Engineers",
number = "2",

}

RIS

TY - JOUR

T1 - Assessing the implications of cellular network performance on mobile content access

AU - Kaup, Fabian

AU - Michelinakis, Foivos

AU - Bui, Nicola

AU - Widmer, Joerg

AU - Wac, Katarzyna

AU - Hausheer, David

PY - 2016

Y1 - 2016

N2 - Mobile applications such as VoIP, (live) gaming, or video streaming have diverse QoS requirements ranging from low delay to high throughput. The optimization of the network quality experienced by end-users requires detailed knowledge of the expected network performance. Also, the achieved service quality is affected by a number of factors, including network operator and available technologies. However, most studies measuring the cellular network do not consider the performance implications of network configuration and management. To this end, this paper reports about an extensive data set of cellular network measurements, focused on analyzing root causes of mobile network performance variability. Measurements conducted on a 4G cellular network in Germany show that management and configuration decisions have a substantial impact on the performance. Specifically, it is observed that the association of mobile devices to a point of presence (PoP) within the operator's network can influence the end-to-end performance by a large extent. Given the collected data, a model predicting the PoP assignment and its resulting RTT leveraging Markov chain and machine learning approaches is developed. RTT increases of 58% to 73% compared to the optimum performance are observed in more than 57% of the measurements. Measurements of the response and page load times of popular websites lead to similar results, namely, a median increase of 40% between the worst and the best performing PoP.

AB - Mobile applications such as VoIP, (live) gaming, or video streaming have diverse QoS requirements ranging from low delay to high throughput. The optimization of the network quality experienced by end-users requires detailed knowledge of the expected network performance. Also, the achieved service quality is affected by a number of factors, including network operator and available technologies. However, most studies measuring the cellular network do not consider the performance implications of network configuration and management. To this end, this paper reports about an extensive data set of cellular network measurements, focused on analyzing root causes of mobile network performance variability. Measurements conducted on a 4G cellular network in Germany show that management and configuration decisions have a substantial impact on the performance. Specifically, it is observed that the association of mobile devices to a point of presence (PoP) within the operator's network can influence the end-to-end performance by a large extent. Given the collected data, a model predicting the PoP assignment and its resulting RTT leveraging Markov chain and machine learning approaches is developed. RTT increases of 58% to 73% compared to the optimum performance are observed in more than 57% of the measurements. Measurements of the response and page load times of popular websites lead to similar results, namely, a median increase of 40% between the worst and the best performing PoP.

KW - 4G mobile communication

KW - Cellular networks

KW - Network measurement

KW - Performance analysis

U2 - 10.1109/TNSM.2016.2544402

DO - 10.1109/TNSM.2016.2544402

M3 - Journal article

AN - SCOPUS:84976495840

VL - 13

SP - 168

EP - 180

JO - IEEE Transactions on Network and Service Management

JF - IEEE Transactions on Network and Service Management

SN - 1932-4537

IS - 2

ER -

ID: 165863667