research-article

An in-depth study of LTE: effect of network protocol and application behavior on performance

Authors:

Subhabrata Sen,

Oliver SpatscheckAuthors Info & Claims

ACM SIGCOMM Computer Communication Review, Volume 43, Issue 4

Pages 363 - 374

https://doi.org/10.1145/2534169.2486006

Published: 27 August 2013 Publication History

Abstract

With lower latency and higher bandwidth than its predecessor 3G networks, the latest cellular technology 4G LTE has been attracting many new users. However, the interactions among applications, network transport protocol, and the radio layer still remain unexplored. In this work, we conduct an in-depth study of these interactions and their impact on performance, using a combination of active and passive measurements. We observed that LTE has significantly shorter state promotion delays and lower RTTs than those of 3G networks. We discovered various inefficiencies in TCP over LTE such as undesired slow start. We further developed a novel and lightweight passive bandwidth estimation technique for LTE networks. Using this tool, we discovered that many TCP connections significantly under-utilize the available bandwidth. On average, the actually used bandwidth is less than 50% of the available bandwidth. This causes data downloads to be longer, and incur additional energy overhead. We found that the under-utilization can be caused by both application behavior and TCP parameter setting. We found that 52.6% of all downlink TCP flows have been throttled by limited TCP receive window, and that data transfer patterns for some popular applications are both energy and network unfriendly. All these findings highlight the need to develop transport protocol mechanisms and applications that are more LTE-friendly.

References

[1]

Netflix App. http://www.netflix.com/.

[2]

Shazam App. http://www.shazam.com/.

[3]

M. Allman, V. Paxson, and E. Blanton. Tcp congestion control. RFC 5681, 2009.

[4]

M. Balakrishnan, I. Mohomed, and V. Ramasubramanian. Where's That Phone?: Geolocating IP Addresses on 3G Networks. In Proceedings of IMC, 2009.

Digital Library

[5]

L. Brakmo and L. Peterson. TCP Vegas: end to end congestion avoidance on a global Internet. Selected Areas in Communications, IEEE Journal on, 13(8):1465 --1480, 1995.

Digital Library

[6]

X. Chen, R. Jin, K. Suh, B. Wang, and W. Wei. Network Performance of Smart Mobile Handhelds in a University Campus WiFi Network. In IMC, 2012.

Digital Library

[7]

J. Erman, A. Gerber, K. Ramakrishnan, S. Sen, and O. Spatscheck. Over The Top Video: The Gorilla in Cellular Networks. In IMC, 2011.

Digital Library

[8]

H. Falaki, R. Mahajan, S. Kandula, D. Lymberopoulos, and R. G. D. Estrin. Diversity in Smartphone Usage. In MobiSys, 2010.

Digital Library

[9]

A. Gember, A. Anand, and A. Akella. A Comparative Study of Handheld and Non-Handheld Traffic in Campus Wi-Fi Networks. In PAM, 2011.

Digital Library

[10]

A. Gerber, J. Pang, O. Spatscheck, and S. Venkataraman. Speed Testing without Speed Tests: Estimating Achievable Download Speed from Passive Measurements. In IMC, 2010.

Digital Library

[11]

E. Halepovic, J. Pang, and O. Spatscheck. Can you GET Me Now? Estimating the Time-to-First-Byte of HTTP Transactions with Passive Measurements. In IMC, 2012.

Digital Library

[12]

N. Hu, L. E. Li, Z. M. Mao, P. Steenkiste, and J. Wang. Locating Internet Bottlenecks: Algorithms, Measurements, and Implications. In SIGCOMM, 2004.

Digital Library

[13]

J. Huang, F. Qian, A. Gerber, Z. M. Mao, S. Sen, and O. Spatscheck. A Close Examination of Performance and Power Characteristics of 4G LTE Networks. In MobiSys, 2012.

Digital Library

[14]

J. Huang, Q. Xu, B. Tiwana, Z. M. Mao, M. Zhang, and P. Bahl. Anatomizing Application Performance Differences on Smartphones. In MobiSys, 2010.

Digital Library

[15]

M. Jain and C. Dovrolis. End-to-End Available Bandwidth: Measurement Methodology, Dynamics, and Relation with TCP Throughput. In IEEE Network, 2003.

Digital Library

[16]

H. Jiang, Y. Wang, K. Lee, and I. Rhee. Tackling Bufferbloat in 3G/4G Networks. In IMC, 2012.

Digital Library

[17]

X. Liu, A. Sridharan, S. Machiraju, M. Seshadri, and H. Zang. Experiences in a 3G Network: Interplay between the Wireless Channel and Applications. In MOBICOM, 2008.

Digital Library

[18]

M. Mathis and J. Mahdavi and S. Floyd and A. Romanow. TCP Selective Acknowledgment Options. RFC 2018, 1996.

Digital Library

[19]

G. Maier, F. Schneider, and A. Feldmann. A First Look at Mobile Hand-held Device Traffic. In PAM, 2010.

Digital Library

[20]

V. Paxson, M. Allman, J. Chu, and M. Sargent. Computing tcp's retransmission timer. RFC 6298, 2011.

[21]

R. Prasad, C. Dovrolis, M. Murray, and kc claffy. Bandwidth Estimation: Metrics, Measurement Techniques, and Tools. In IEEE Network, 2003.

Digital Library

[22]

F. Qian, A. Gerber, Z. M. Mao, S. Sen, O. Spatscheck, and W. Willinger. TCP Revisited: A Fresh Look at TCP in the Wild. In IMC, 2009.

Digital Library

[23]

F. Qian, J. Huang, J. Erman, Z. M. Mao, S. Sen, and O. Spatscheck. How to Reduce Smartphone Traffic Volume by 30%? In PAM, 2013.

Digital Library

[24]

F. Qian, Z. Wang, Y. Gao, J. Huang, A. Gerber, Z. M. Mao, S. Sen, and O. Spatscheck. Periodic Transfers in Mobile Applications: Network-wide Origin, Impact, and Optimization. In World Wide Web, 2012.

Digital Library

[25]

F. Qian, Z. Wang, A. Gerber, Z. M. Mao, S. Sen, and O. Spatscheck. Characterizing Radio Resource Allocation for 3G Networks. In IMC, 2010.

Digital Library

[26]

F. Qian, Z. Wang, A. Gerber, Z. M. Mao, S. Sen, and O. Spatscheck. Profiling Resource Usage for Mobile Applications: a Cross-layer Approach. In MobiSys, 2011.

Digital Library

[27]

R. Braden. Requirements for Internet Hosts -- Communication Layers. RFC 1122, 1989.

Digital Library

[28]

P. Sarolahti and A. Kuznetsov. Congestion Control in Linux TCP. In USENIX Annual Technical Conference, 2002.

Digital Library

[29]

S. Sesia, I. Toufik, and M. Baker. LTE: The UMTS Long Term Evolution From Theory to Practice. John Wiley and Sons, Inc., 2009.

Digital Library

[30]

C. Shepard, A. Rahmati, C. Tossell, L. Zhong, and P. Kortum. LiveLab: Measuring Wireless Networks and Smartphone Users in the Field. In HotMetrics, 2010.

Digital Library

[31]

J. Sommers and P. Barford. Cell vs. WiFi: On the Performance of Metro Area Mobile Connections. In IMC, 2012.

Digital Library

[32]

V. Jacobson and R. Braden and D. Borman. TCP Extensions for High Performance. RFC 1323, 1992.

Digital Library

[33]

Z. Wang, Z. Qian, Q. Xu, Z. M. Mao, and M. Zhang. An Untold Story of Middleboxes in Cellular Networks. In SIGCOMM, 2011.

Digital Library

[34]

Q. Xu, J. Erman, A. Gerber, Z. M. Mao, J. Pang, and S. Venkataraman. Identifying Diverse Usage Behaviors of Smartphone Apps. In IMC, 2011.

Digital Library

[35]

Q. Xu, J. Huang, Z. Wang, F. Qian, A. Gerber, and Z. M. Mao. Cellular Data Network Infrastructure Characterization and Implication on Mobile Content Placement. In SIGMETRICS, 2011.

Digital Library

[36]

Y. Zhang, L. Breslau, V. Paxson, and S. Shenker. On the Characteristics and Origins of Internet Flow Rates. In SIGCOMM, 2002.

Digital Library

[37]

Z. Zhuang, T.-Y. Chang, R. Sivakumar, and A. Velayutham. A3: Application-Aware Acceleration for Wireless Data Networks. In MOBICOM, 2006.

Digital Library

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https://dl.acm.org/doi/10.1145/3651890.3672269
Feng YChen SXi WWang SZhao JGong W(2024)Heartbeating with LTE Networks for Ambient BackscatterIEEE Transactions on Mobile Computing10.1109/TMC.2023.3290298(1-12)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3290298
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An in-depth study of LTE: effect of network protocol and application behavior on performance

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Published In

cover image ACM SIGCOMM Computer Communication Review

ACM SIGCOMM Computer Communication Review Volume 43, Issue 4

October 2013

595 pages

ISSN:0146-4833

DOI:10.1145/2534169

Issue’s Table of Contents

SIGCOMM '13: Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
August 2013
580 pages
ISBN:9781450320566
DOI:10.1145/2486001
General Chairs:
Dah Ming Chiu
Chinese University of Hong Kong, China
,
Jia Wang
AT&T Labs - Research, USA
,
Program Chairs:
Paul Barford
University of Wisconsin, USA
,
Srinivasan Seshan
Carnegie Mellon University, USA

Copyright © 2013 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 August 2013

Published in SIGCOMM-CCR Volume 43, Issue 4

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Cited By

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https://dl.acm.org/doi/10.1145/3651890.3672269
Feng YChen SXi WWang SZhao JGong W(2024)Heartbeating with LTE Networks for Ambient BackscatterIEEE Transactions on Mobile Computing10.1109/TMC.2023.3290298(1-12)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3290298
Kato TFukumoto NSasaki CTagami ANakao A(2024)Challenges of CPS/IoT Network Architecture in 6G EraIEEE Access10.1109/ACCESS.2024.339536312(62804-62817)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3395363
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