The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
A first look at traffic on smartphones
Abstract
Using data from 43 users across two platforms, we present a detailed look at smartphone traffic. We find that browsing contributes over half of the traffic, while each of email, media, and maps contribute roughly 10%. We also find that the overhead of lower layer protocols is high because of small transfer sizes. For half of the transfers that use transport-level security, header bytes correspond to 40% of the total. We show that while packet loss is the main factor that limits the throughput of smartphone traffic, larger send buffers at Internet servers can improve the throughput of a quarter of the transfers. Finally, by studying the interaction between smartphone traffic and the radio power management policy, we find that the power consumption of the radio can be reduced by 35% with minimal impact on the performance of packet exchanges.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Energy consumption in mobile phones: a measurement study and implications for network applications
Balasubramanian, N., Balasubramanian, A., & Venkataramani, A. (2009) · Proceedings of the 9th ACM SIGCOMM conference on Internet measurement · doi:10.1145/1644893.1644927 · Cited by 1,101
Falaki, H., Mahajan, R., Kandula, S., Lymberopoulos, D., Govindan, R., & Estrin, D. (2010) · Proceedings of the 8th international conference on Mobile systems, applications, and services · doi:10.1145/1814433.1814453 · Cited by 838
Self-citationOn dominant characteristics of residential broadband internet traffic
Maier, G., Feldmann, A., Paxson, V., & Allman, M. (2009) · Proceedings of the 9th ACM SIGCOMM conference on Internet measurement · doi:10.1145/1644893.1644904 · Cited by 425
Shye, A., Scholbrock, B., & Memik, G. (2009) · Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture · doi:10.1145/1669112.1669135 · Cited by 344
On the characteristics and origins of internet flow rates
Zhang, Y., Breslau, L., Paxson, V., & Shenker, S. (2002) · Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications · doi:10.1145/633025.633055 · Cited by 325
Anatomizing application performance differences on smartphones
Huang, J., Xu, Q., Tiwana, B., Mao, Z. M., Zhang, M., & Bahl, P. (2010) · Proceedings of the 8th international conference on Mobile systems, applications, and services · doi:10.1145/1814433.1814452 · Cited by 296
Measuring serendipity: connecting people, locations and interests in a mobile 3G network
Trestian, I., Ranjan, S., Kuzmanovic, A., & Nucci, A. (2009) · Proceedings of the 9th ACM SIGCOMM conference on Internet measurement · doi:10.1145/1644893.1644926 · Cited by 170
Internet Traffic Characterization
claffy, K. (1994) · Cited by 84
Performance optimizations for wireless wide-area networks
Chakravorty, R., Banerjee, S., Rodríguez, P., et al. (2004) · Proceedings of the 28th Annual International Conference on Mobile Computing And Networking · doi:10.1145/1023720.1023737 · Cited by 59
Cited by
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities
Capponi, A., Fiandrino, C., Kantarci, B., Foschini, L., Kliazovich, D., & Bouvry, P. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2914030 · Cited by 594
Robust Smartphone App Identification via Encrypted Network Traffic Analysis
Taylor, V. F., Spolaor, R., Conti, M., & Martinovic, I. (2018) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2017.2737970 · Cited by 439
Identifying diverse usage behaviors of smartphone apps
Xu, Q., Erman, J., Gerber, A., Mao, Z., Pang, J., & Venkataraman, S. (2011) · Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference · doi:10.1145/2068816.2068847 · Cited by 414
Green IoT: An Investigation on Energy Saving Practices for 2020 and Beyond
Arshad, R., Zahoor, S., Shah, M. A., Wahid, A., & Yu, H. (2017) · IEEE Access · doi:10.1109/access.2017.2686092 · Cited by 372
“Many methods were introduced in [57] for the improvement of the power consumption and performance of the smart phones.”
MethodSmartphone Internet access and use: Extending the digital divide and usage gap
Tsetsi, E., & Rains, S. A. (2017) · Mobile Media & Communication · doi:10.1177/2050157917708329 · Cited by 292
Metadata
- Authors
- Falaki, H., Lymberopoulos, D., Mahajan, R., Kandula, S., & Estrin, D.
- Venue
- Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
- Publisher
- ACM
- Published
- 2010-11
- Pages
- 281-287
- OpenAlex
- W1983750266
- Cited by
- 388
- References
- 9
- FWCI
- 36.72
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A first look at traffic on smartphones. https://app.cochat.ai/papers/10.1145/1879141.1879176
- The paper
- Falaki, H., Lymberopoulos, D., Mahajan, R., Kandula, S., & Estrin, D. (2010). A first look at traffic on smartphones. Proceedings of the 10th ACM SIGCOMM conference on Internet measurement. https://doi.org/10.1145/1879141.1879176
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
