More Web Proxy on the site http://driver.im/

research-article

Mobile data offloading: how much can WiFi deliver?

Authors:

Song ChongAuthors Info & Claims

Co-NEXT '10: Proceedings of the 6th International COnference

Article No.: 26, Pages 1 - 12

https://doi.org/10.1145/1921168.1921203

Published: 30 November 2010 Publication History

Abstract

This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited about 100 iPhone users from metropolitan areas and collected statistics on their WiFi connectivity during about a two and half week period in February 2010. Our trace-driven simulation using the acquired traces indicates that WiFi already offloads about 65% of the total mobile data traffic and saves 55% of battery power without using any delayed transmission. If data transfers can be delayed with some deadline until users enter a WiFi zone, substantial gains can be achieved only when the deadline is fairly larger than tens of minutes. With 100 second delays, the achievable gain is less than only 2--3%. But with 1 hour or longer deadline, traffic and energy saving gains increase beyond 29% and 20%, respectively. These results are in stark contrast to the substantial gain (20 to 33%) reported by the existing work even for 100 second delayed transmission using traces taken from transit buses or war-driving. The major performance difference comes from traces: while bus and war-driving traces contain much shorter connection and inter-connection times, our traces reflects the daily mobility patterns of average users more accurately.

References

[1]

Urban tomography project. http://tomography.usc.edu/.

[2]

Cisco visual networking index: Global mobile data traffic forecast update, 2009-2014, February 2010. http://www.cisco.com/en/US/solutions/collateral/ns341/ns525/ns537/ns705/ns827/white_paper.c11-520862.html.

[3]

Data, data everywhere, February 2010. http://www.economist.com/specialreports/displayStory.cfm?story.id=15557443.

[4]

A. Abhari and M. Soraya. Workload generation for youtube. Multimedia Tools and Applications, 46(1):91--118, 2010.

Digital Library

[5]

R. Ahmad and Z. Lin. Context-for-wireless: context-sensitive energy-efficient wireless data transfer. In Proceedings of ACM MobiSys, 2007.

Digital Library

[6]

A. Balasubramanian, R. Mahajan, and A. Venkataramani. Augmenting mobile 3g using wifi. In Proceedings of ACM MobiSys, 2010.

Digital Library

[7]

N. Balasubramanian, A. Balasubramanian, and A. Venkataramani. Energy consumption in mobile phones: a measurement study and implications for network applications. In Proceedings of ACM SIGCOMMIMC, 2009.

Digital Library

[8]

A.-L. Barabasi. The origin of bursts and heavy tails in human dynamics. Nature, 435:207--211, May 2005.

[9]

A. Chaintreau, P. Hui, J. Crowcroft, C. Diot, R. Gass, and J. Scott. Impact of human mobility on the design of opportunistic forwarding algorithms. In Proceedings of IEEE INFOCOM, 2006.

[10]

I. Constandache, R. R. Choudhury, and I. Rhee. Towards mobile phone localization without war-driving. In Proceedings of IEEE INFOCOM, 2010.

Digital Library

[11]

R. Gass and C. Diot. An experimental performance comparison of 3G and WiFi. In Proceedings of ACM PAM, 2010.

Digital Library

[12]

D. Han, M. Kaminsky, A. Agarwala, K. Papagiannaki, D. G. Andersen, and S. Seshan. Mark-and-Sweep: Getting the "inside" scoop on neighborhood networks. In Proceedings of ACM IMC (short paper), 2008.

Digital Library

[13]

T. Kaneshige. AT&T iPhone users irate at idea of usage-based pricing, December 2009. http://www.pcworld.com/article/184589/atandt_iphone_users_irate_at_idea_of_usagebased_pricing.html.

[14]

T. Karagiannis, J.-Y. L. Boudec, and M. Vojnovic. Power law and exponential decay of inter contact times between mobile devices. In Proceedings of ACM MOBICOM, 2007.

Digital Library

[15]

A. J. Nicholson and B. D. Noble. Breadcrumbs: forecasting mobile connectivity. In Proceedings of ACM MOBICOM, 2008.

Digital Library

[16]

M.-R. Ra, J. Paek, A. B. Sharma, R. Govindan, M. H. Krieger, and M. J. Neely. Energy-delay tradeoffs in smartphone applications. In Proceedings of ACM MobiSys, 2010.

Digital Library

[17]

M. Reardon. Cisco predicts wireless-data explosion, Feburay 2010. http://news.cnet.com/8301-30686_3-10449758-266.html.

[18]

I. Rhee, M. Shin, S. Hong, K. Lee, and S. Chong. On the levy walk nature of human mobility. In Proceedings of IEEE INFOCOM, 2008.

[19]

A. Sharma, V. Navda, R. Ramjee, V. N. Padmanabhan, and E. M. Belding. Cool-tether: energy efficient on-the-fly wifi hot-spots using mobile phones. In ACM CoNEXT, 2009.

Digital Library

[20]

A. Thiagarajan, L. Ravindranath, K. LaCurts, S. Madden, H. Balakrishnan, S. Toledo, and J. Eriksson. VTrack: accurate, energy-aware road traffic delay estimation using mobile phones. In Proceedings of ACM SenSys, 2009.

Digital Library

Cited By

Hasan MJahan NNazri MIslam SAttique Khan MAlzahrani AAlalwan NNam Y(2024)Federated Learning for Computational Offloading and Resource Management of Vehicular Edge Computing in 6G-V2X NetworkIEEE Transactions on Consumer Electronics10.1109/TCE.2024.335753070:1(3827-3847)Online publication date: 26-Jan-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3357530
Bouloukakis GGeorgantas NKattepur AHassan HIssarny V(2024)Automating the Evaluation of Interoperability Effectiveness in Heterogeneous IoT Systems2024 IEEE 21st International Conference on Software Architecture (ICSA)10.1109/ICSA59870.2024.00014(58-68)Online publication date: 4-Jun-2024
https://doi.org/10.1109/ICSA59870.2024.00014
Kamath SAravinda Raman JKumar PSingh SSathish Kumar M(2024)SDN-Based Multipath Data Offloading Scheme Using Link Quality Prediction for LTE and WiFi NetworksIEEE Access10.1109/ACCESS.2024.350603612(176554-176568)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3506036
Show More Cited By

Index Terms

Mobile data offloading: how much can WiFi deliver?

Recommendations

Mobile data traffic offloading over Passpoint hotspots

Wi-Fi technology has always been an attractive solution for catering the increasing data demand in mobile networks because of the availability of Wi-Fi networks, the high bit rates they provide, and the lower cost of ownership. However, the legacy WiFi ...
Mobile data offloading: how much can WiFi deliver?

This paper presents a quantitative study on the performance of 3G mobile data offloading through WiFi networks. We recruited 97 iPhone users from metropolitan areas and collected statistics on their WiFi connectivity during a two-and-a-halfweek period ...
Mobile Data Offloading: A Host-Based Distributed Mobility Management Approach

The increasing use of mobile devices has resulted in an explosion in mobile Internet traffic. To cope with this growth, mobile network architectures are becoming flatter, and IP mobility support protocols must evolve along with them. The authors propose ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

Co-NEXT '10: Proceedings of the 6th International COnference

November 2010

349 pages

ISBN:9781450304481

DOI:10.1145/1921168

Conference Chairs:
Jaudelice de Oliveira
Drexel University
,
Maximilian Ott
NICTA, Australia
,
Program Chairs:
Tim Griffin
University of Cambridge
,
Muriel Medard
Massachusetts Institute of Technology

Copyright © 2010 ACM.

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

SIGCOMM: ACM Special Interest Group on Data Communication

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 November 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Research-article

Funding Sources

Conference

Co-NEXT '10

Sponsor:

SIGCOMM

Co-NEXT '10: Conference on emerging Networking EXperiments and Technologies

November 30 - December 3, 2010

Pennsylvania, Philadelphia

Acceptance Rates

Overall Acceptance Rate 198 of 789 submissions, 25%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

81
Total Citations
View Citations
2,696
Total Downloads

Downloads (Last 12 months)27
Downloads (Last 6 weeks)0

Reflects downloads up to 01 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Hasan MJahan NNazri MIslam SAttique Khan MAlzahrani AAlalwan NNam Y(2024)Federated Learning for Computational Offloading and Resource Management of Vehicular Edge Computing in 6G-V2X NetworkIEEE Transactions on Consumer Electronics10.1109/TCE.2024.335753070:1(3827-3847)Online publication date: 26-Jan-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3357530
Bouloukakis GGeorgantas NKattepur AHassan HIssarny V(2024)Automating the Evaluation of Interoperability Effectiveness in Heterogeneous IoT Systems2024 IEEE 21st International Conference on Software Architecture (ICSA)10.1109/ICSA59870.2024.00014(58-68)Online publication date: 4-Jun-2024
https://doi.org/10.1109/ICSA59870.2024.00014
Kamath SAravinda Raman JKumar PSingh SSathish Kumar M(2024)SDN-Based Multipath Data Offloading Scheme Using Link Quality Prediction for LTE and WiFi NetworksIEEE Access10.1109/ACCESS.2024.350603612(176554-176568)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3506036
Layton RWitkowski D(2021)5G Versus Wi-Fi: Challenges for Economic, Spectrum, and Security PolicyJournal of Information Policy10.5325/jinfopoli.11.2021.052311(523-561)Online publication date: 1-Dec-2021
https://doi.org/10.5325/jinfopoli.11.2021.0523
Bouloukakis GGeorgantas NKattepur AIssarny V(2021)Timed protocol analysis of interconnected mobile IoT devicesJournal of Internet Services and Applications10.1186/s13174-021-00143-w12:1Online publication date: 1-Dec-2021
https://doi.org/10.1186/s13174-021-00143-w
Rothchild DPanda AUllah EIvkin NStoica IBraverman VGonzalez JArora RDaumé HSingh A(2020)FetchSGDProceedings of the 37th International Conference on Machine Learning10.5555/3524938.3525702(8253-8265)Online publication date: 13-Jul-2020
https://dl.acm.org/doi/10.5555/3524938.3525702
Agamy AMohamed A(2020)Impact of Offloading on the Efficiency of Wireless Access NetworksInternational Journal of Wireless Information Networks10.1007/s10776-020-00498-0Online publication date: 3-Oct-2020
https://doi.org/10.1007/s10776-020-00498-0
Rossi FSevero de Souza PMarques WCalheiros RRodrigues G(2019)Network Support for IoT EcosystemsEnabling Technologies and Architectures for Next-Generation Networking Capabilities10.4018/978-1-5225-6023-4.ch009(197-213)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-6023-4.ch009
Bertier CDias de Amorim MBenbadis FConan VLoureiro AKanhere SBellavista P(2019)Modeling Realistic Bit Rates of D2D Communications between Android DevicesProceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems10.1145/3345768.3355918(315-322)Online publication date: 25-Nov-2019
https://dl.acm.org/doi/10.1145/3345768.3355918
Cui YJiang YLai ZChen XHu YTan KDai MZheng KLi Y(2019)Wireless Network Instabilities in the WildIEEE/ACM Transactions on Networking10.1109/TNET.2018.288587227:1(214-230)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1109/TNET.2018.2885872
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents