skip to main content
10.1145/1814433.1814452acmconferencesArticle/Chapter ViewAbstractPublication PagesmobisysConference Proceedingsconference-collections
research-article

Anatomizing application performance differences on smartphones

Published: 15 June 2010 Publication History

Abstract

The use of cellular data networks is increasingly popular due to the widespread deployment of 3G technologies and the rapid adoption of smartphones, such as iPhone and GPhone. Besides email and web browsing, a variety of network applications are now available, rendering smartphones potentially useful substitutes for their desktop counterparts. Nevertheless, the performance of smartphone applications in the wild is still poorly understood due to a lack of systematic measurement methodology.
We identify and study important factors that impact user-perceived performance of network applications on smartphones. We develop a systematic methodology for comparing this performance along several key dimensions such as carrier networks, device capabilities, and server configurations. To ensure a fair and representative comparison, we conduct controlled experiments, informed by data collected through 3GTest, a cross-platform measurement tool we designed, executed by more than 30,000 users from all over the world. Our work is an essential step towards understanding the performance of smartphone applications from the perspective of users, application developers, cellular network operators, and smartphone vendors. Our analysis culminates with a set of recommendations that can lead to better application design and infrastructure support for smartphone users.

References

[1]
Alexa Top 500 Global Sites. http://www.alexa.com/topsites.
[2]
Best Practices for Speeding Up Your Web Site. http://developer.yahoo.com/performance/rules.html#minify.
[3]
Canalys Press Release: R2009112. http://www.canalys.com/pr/2009/r2009112.htm.
[4]
FCC Consumer Broadband Test. http://broadband.gov/qualitytest/.
[5]
ICSI Netalyzr. http://netalyzr.icsi.berkeley.edu/.
[6]
Smartphone 3G Test (3GTest). http://www.eecs.umich.edu/3gtest.
[7]
Speedtest.net. http://www.speedtest.net/.
[8]
SunSpider JavaScript Benchmark. http://www2.webkit.org/perf/sunspider-0.9/sunspider.html.
[9]
M. Balakrishnan, I. Mohomed, and V. Ramasubramanian. Where's That Phone?: Geolocating IP Addresses on 3G Networks. In Proceedings of IMC, 2009.
[10]
R. Chakravorty, S. Banerjee, P. Rodriguez, J. Chesterfield, and I. Pratt. Performance Optimizations for Wireless Wide-Area Networks: Comparative Study and Experimental Evaluation. In Proceedings of ACM MOBICOM, 2004.
[11]
M. C. Chan and R. Ramjee. TCP/IP Performance over 3G Wireless Links with Rate and Delay Variation. In Proc. of MOBICOM, 2002.
[12]
J. Chesterfield, R. Chakravorty, J. Crowcroft, P. Rodriguez, and S. Banerjee. Experiences with Multimedia Streaming over 2.5G and 3G Networks. Journal ACM/MONET, 2004.
[13]
M. Ghaderi, A. Sridharan, H. Zang, D. Towsley, and R. Cruz. Modeling TCP in a Multi-Rate Multi-User CDMA System. In IFIP-Networking 2007, 2007.
[14]
K. Jang, M. Han, S. Cho, H.-K. Ryu, J. Lee, Y. Lee, and S. B. Moon. 3G and 3.5G Wireless Network Performance Measured from Moving Cars and High-speed Trains. In Proc. of ACM MICNET, 2009.
[15]
L. Masinter. The "data" URL Scheme. RFC 2397, 1998.
[16]
X. Liu, A. Sridharan, S. Machiraju, M. Seshadri, and H. Zang. Experiences in a 3G Network: Interplay between the Wireless Channel and Applications. In Proceedings of ACM MOBICOM, 2008.
[17]
R. Mahajan, M. Zhang, L. Poole, and V. Pai. Uncovering Performance Differences in Backbone ISPs with Netdiff. In Proceeding of NSDI, 2008.
[18]
K. Mattar, A. Sridharan, H. Zang, I. Matta, and A. Bestavros. TCP Over CDMA2000 Networks : A Cross-Layer Measurement Study. In PAM, 2007.
[19]
J. Padhye, V. Firoiu, D. Towsley, and J. Kurose. Modeling TCP Throughput: A Simple Model and its Empirical Validation. In Proc. ACM SIGCOMM, 1998.
[20]
W. L. Tan, F. Lam, and W.-C. Lau. An empirical study on 3g network capacity and performance. In Proc. IEEE INFOCOM, 2007.
[21]
I. Trestian, S. Ranjan, A. Kuzmanovic, and A. Nucci. Measuring Serendipity: Connecting People, Locations and Interests in a Mobile 3G Network. In Proceedings of IMC, 2009.
[22]
W. Wei, C. Zhang, H. Zang, J. Kurose, and D. Towsley. Inference and Evaluation of Split-Connection Approaches in Cellular Data Networks. In PAM, 2006.
[23]
D. Willkomm, S. Machiraju, J. Bolot, and A. Wolisz. Primary Users in Cellular Networks: A Large-scale Measurement Study. In DySpAN, 2008.
[24]
Z. Zhuang, T.-Y. Chang, R. Sivakumar, and A. Velayutham. A3: Application-Aware Acceleration for Wireless Data Networks. In Proc. of ACM MOBICOM, 2006.

Cited By

View all
  • (2024)SODA: An Adaptive Bitrate Controller for Consistent High-Quality Video StreamingProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672260(613-644)Online publication date: 4-Aug-2024
  • (2024)Understanding and Detecting Inefficient Image Displaying Issues in Android AppsJournal of Computer Science and Technology10.1007/s11390-022-1670-339:2(434-459)Online publication date: 1-Mar-2024
  • (2023)A Worldwide Look Into Mobile Access Networks Through the Eyes of AmiGos2023 7th Network Traffic Measurement and Analysis Conference (TMA)10.23919/TMA58422.2023.10198920(1-10)Online publication date: 26-Jun-2023
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
MobiSys '10: Proceedings of the 8th international conference on Mobile systems, applications, and services
June 2010
382 pages
ISBN:9781605589855
DOI:10.1145/1814433
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]

Sponsors

In-Cooperation

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 June 2010

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. 3G network
  2. application performance
  3. mobile web browsing
  4. performance comparison
  5. smartphone

Qualifiers

  • Research-article

Conference

MobiSys'10
Sponsor:

Acceptance Rates

Overall Acceptance Rate 274 of 1,679 submissions, 16%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)40
  • Downloads (Last 6 weeks)4
Reflects downloads up to 13 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2024)SODA: An Adaptive Bitrate Controller for Consistent High-Quality Video StreamingProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672260(613-644)Online publication date: 4-Aug-2024
  • (2024)Understanding and Detecting Inefficient Image Displaying Issues in Android AppsJournal of Computer Science and Technology10.1007/s11390-022-1670-339:2(434-459)Online publication date: 1-Mar-2024
  • (2023)A Worldwide Look Into Mobile Access Networks Through the Eyes of AmiGos2023 7th Network Traffic Measurement and Analysis Conference (TMA)10.23919/TMA58422.2023.10198920(1-10)Online publication date: 26-Jun-2023
  • (2023)DroidPerf: Profiling Memory Objects on Android DevicesProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3592503(1-15)Online publication date: 2-Oct-2023
  • (2022)Mobile access bandwidth in practiceProceedings of the ACM SIGCOMM 2022 Conference10.1145/3544216.3544237(114-128)Online publication date: 22-Aug-2022
  • (2022)A Survey of Performance Optimization for Mobile ApplicationsIEEE Transactions on Software Engineering10.1109/TSE.2021.307119348:8(2879-2904)Online publication date: 1-Aug-2022
  • (2022)Investigating the Predictability of QoS Metrics in Cellular Networks2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)10.1109/IWQoS54832.2022.9812881(1-10)Online publication date: 10-Jun-2022
  • (2022)On the Performance of Cloud-Based mHealth Applications: A Methodology on Measuring Service Response Time and a Case StudyIEEE Access10.1109/ACCESS.2022.317485510(53208-53224)Online publication date: 2022
  • (2022)Generation of realistic cloud access times for mobile application testing using transfer learningComputer Communications10.1016/j.comcom.2021.03.010172:C(196-215)Online publication date: 23-Apr-2022
  • (2021)Improving Signal-Strength Aggregation for Mobile Crowdsourcing ScenariosSensors10.3390/s2104108421:4(1084)Online publication date: 5-Feb-2021
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media