research-article

An Empirical Analysis of a Large-scale Mobile Cloud Storage Service

Authors:

Ningjing Huang,

Mohamed Ali Kaafar,

Peter SteenkisteAuthors Info & Claims

IMC '16: Proceedings of the 2016 Internet Measurement Conference

Pages 287 - 301

https://doi.org/10.1145/2987443.2987465

Published: 14 November 2016 Publication History

Abstract

Cloud storage services are serving a rapidly increasing number of mobile users. However, little is known about the differences between mobile and traditional cloud storage services at scale. In order to understand mobile user access behavior, we analyzed a dataset of 350 million HTTP request logs from a large-scale mobile cloud storage service. This paper presents our results and discusses the implications for system design and network performance. Our key observation is that the examined mobile cloud storage service is dominated by uploads, and the vast majority of users rarely retrieve their uploads during the one-week observation period. In other words, mobile users lean towards the usage of cloud storage for backup. This suggests that delta encoding and chunk-level deduplication found in traditional cloud storage services can be reasonably omitted in mobile scenarios. We also observed that the long idle time between chunk transmissions by Android clients should be shortened since they cause significant performance degradation due to the restart of TCP slow-start. Other observations related to session characteristics, load distribution, user behavior and engagement, and network performance.

References

[1]

Rfc5681: Tcp congestion control. https://www.ietf.org/rfc/rfc5681.txt, 2009.

[2]

Rfc6298: Computing tcp's retransmission timer. https://www.ietf.org/rfc/rfc6298.txt, 2011.

[3]

Rfc6298: Tcp extensions for high performance. https://tools.ietf.org/html/rfc7323, 2014.

[4]

Dropbox highlights. https://www.dropbox.com/news, 2016.

[5]

World personal cloud market, 2014 -2020. https://www.iedmarketresearch.com/personal-cloud-market, 2016.

[6]

A. Balasubramanian, N. Balasubramanian, S. J. Huston, D. Metzler, and D. J. Wetherall. Findall: A local search engine for mobile phones. In Proceedings of the ACM CoNEXT, 2012.

Digital Library

[7]

T. Benaglia, D. Chauveau, D. R. Hunter, and D. S. Young. mixtools: An r package for analyzing mixture models. Journal of Statistical Software, 32(6), 2009.

[8]

E. Bocchi, I. Drago, and M. Mellia. Personal cloud storage: Usage, performance and impact of terminals. In Proceedings of the IEEE CloudNet, 2015.

[9]

X. Chen, R. Jin, K. Suh, B. Wang, and W. Wei. Network performance of smart mobile handhelds in a university campus wifi network. In Proceedings of the ACM IMC, 2012.

Digital Library

[10]

Y. Cui, Z. Lai, X. Wang, N. Dai, and C. Miao. Quicksync: Improving synchronization efficiency for mobile cloud storage services. In Proceedings of the ACM MobiCom, 2015.

Digital Library

[11]

I. Drago, E. Bocchi, M. Mellia, H. Slatman, and A. Pras. Benchmarking personal cloud storage. In Proceedings of the ACM IMC, 2013.

Digital Library

[12]

I. Drago, M. Mellia, M. M. Munafo, A. Sperotto, R. Sadre, and A. Pras. Inside dropbox: Understanding personal cloud storage services. In Proceedings of the ACM IMC, 2012.

Digital Library

[13]

T. Flach, N. Dukkipati, A. Terzis, B. Raghavan, N. Cardwell, Y. Cheng, A. Jain, S. Hao, E. Katz-Bassett, and R. Govindan. Reducing web latency: The virtue of gentle aggression. In Proceedings of the ACM SIGCOMM, 2013.

Digital Library

[14]

G. Goncalves, I. Drago, A. Couto da Silva, A. Borges Vieira, and J. Almeida. Modeling the dropbox client behavior. In Proceedings of IEEE ICC, 2014.

[15]

R. Gracia-Tinedo, M. Sanchez Artigas, A. Moreno-Martinez, C. Cotes, and P. Garcia Lopez. Actively measuring personal cloud storage. In Proceedings of IEEE CLOUD, 2013.

Digital Library

[16]

R. Gracia-Tinedo, Y. Tian, J. Sampé, H. Harkous, J. Lenton, P. García-López, M. Sánchez-Artigas, and M. Vukolic. Dissecting ubuntuone: Autopsy of a global-scale personal cloud back-end. In Proceedings of the ACM IMC, 2015.

Digital Library

[17]

L. Guo, E. Tan, S. Chen, X. Zhang, and Y. E. Zhao. Analyzing patterns of user content generation in online social networks. In Proceedings of the ACM KDD, 2009.

Digital Library

[18]

A. Halfaker, O. Keyes, D. Kluver, J. Thebault-Spieker, T. Nguyen, K. Shores, A. Uduwage, and M. Warncke-Wang. User session identification based on strong regularities in inter-activity time. In Proceedings of the International Conference on WWW, 2015.

Digital Library

[19]

Y. Huang, Z. Li, G. Liu, and Y. Dai. Cloud download: Using cloud utilities to achieve high-quality content distribution for unpopular videos. In Proceedings of the ACM MM, 2011.

Digital Library

[20]

N. P. Jewell. Mixtures of exponential distributions. Ann. Statist., 10(2), 06 1982.

[21]

Z. Li, C. Jin, T. Xu, C. Wilson, Y. Liu, L. Cheng, Y. Liu, Y. Dai, and Z.-L. Zhang. Towards network-level efficiency for cloud storage services. In Proceedings of the ACM IMC, 2014.

Digital Library

[22]

Z. Li, C. Wilson, Z. Jiang, Y. Liu, B. Zhao, C. Jin, Z.-L. Zhang, and Y. Dai. Efficient batched synchronization in dropbox-like cloud storage services. In Proceedings of the ACM/IFIP/USENIX Middleware, 2013.

[23]

Z. Li, C. Wilson, T. Xu, Y. Liu, Z. Lu, and Y. Wang. Offline downloading in china: A comparative study. In Proceedings of the ACM IMC, 2015.

Digital Library

[24]

S. Liu, X. Huang, H. Fu, and G. Yang. Understanding data characteristics and access patterns in a cloud storage system. In Proceedings of the IEEE/ACM CCGrid, 2013.

[25]

L. Muchnik, S. Pei, L. C. Parra, S. D. S. Reis, J. Andrade Jr, S. Havlin, and H. A. Makse. Origins of power-law degree distribution in the heterogeneity of human activity in social networks. Scientific Reports, 3, 2013.

[26]

S. Muralidhar, W. Lloyd, S. Roy, C. Hill, E. Lin, W. Liu, S. Pan, S. Shankar, V. Sivakumar, L. Tang, and S. Kumar. f4: Facebook\textquoterights warm blob storage system. In Proceedings of the OSDI, 2014.

Digital Library

[27]

T. Qiu, Z. Ge, S. Lee, J. Wang, J. Xu, and Q. Zhao. Modeling user activities in a large iptv system. In Proceedings of the ACM IMC, 2009.

Digital Library

[28]

V. Visweswaraiah and J. Heidemann. Improving restart of idle TCP connections. Technical report, University of Southern California, Computer Science Department, 1997.

[29]

Y. Zhang, L. Qiu, and S. Keshav. Optimizing tcp start-up performance. Technical report, Cornell University, Computer Science, 1999.

Digital Library

[30]

J. Zhou, Q. Wu, Z. Li, S. Uhlig, P. Steenkiste, J. Chen, and G. Xie. Demystifying and mitigating tcp stalls at the server side. In Proceedings of the ACM CoNext, 2015.

Digital Library

Cited By

Mishra SZanella AMartínez-Durive OMadariaga DZiemlicki CFiore M(2024)Characterizing 5G Adoption and its Impact on Network Traffic and Mobile Service ConsumptionIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621344(1531-1540)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621344
Zheng JLi ZQiu YLin HXiao HLi YLiu Y(2022)WebAssembly-based Delta Sync for Cloud Storage ServicesACM Transactions on Storage10.1145/350284718:3(1-31)Online publication date: 21-Sep-2022
https://dl.acm.org/doi/10.1145/3502847
Ando RKadobayashi YTakakura H(2021)Choice of parallelism: multi-GPU driven pipeline for huge academic backbone networkInternational Journal of Parallel, Emergent and Distributed Systems10.1080/17445760.2021.194100936:6(609-622)Online publication date: 24-Jun-2021
https://doi.org/10.1080/17445760.2021.1941009
Show More Cited By

Index Terms

An Empirical Analysis of a Large-scale Mobile Cloud Storage Service
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Empirical studies in ubiquitous and mobile computing
2. Networks
  1. Network performance evaluation
    1. Network measurement
  2. Network services
    1. Cloud computing

Recommendations

Mobile cloud storage: a contextual experience
MobileHCI '14: Proceedings of the 16th international conference on Human-computer interaction with mobile devices & services

In an increasingly connected world, users access personal or shared data, stored "in the cloud" (e.g., Dropbox, Skydrive, iCloud) with multiple devices. Despite the popularity of cloud storage services, little work has focused on investigating cloud ...
It's in the Cloud: Theorizing Context-Specific Factors Influencing the Perception of Mobile Cloud Storage

This paper examines the impact of mobile device characteristics on perceptions of cloud storage. Following the framework and guidelines for context-specific theorizing in information systems research, we develop and test a model that examines the ...
LSM-tree managed storage for large-scale key-value store
SoCC '17: Proceedings of the 2017 Symposium on Cloud Computing

Key-value stores are increasingly adopting LSM-trees as their enabling data structure in the backend storage, and persisting their clustered data through a file system. A file system is expected to not only provide file/directory abstraction to organize ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

IMC '16: Proceedings of the 2016 Internet Measurement Conference

November 2016

570 pages

ISBN:9781450345262

DOI:10.1145/2987443

General Chairs:
Phillipa Gill
University of Massachusetts--Amherst
,
John Heidemann
USC/ISI
,
Program Chairs:
John W. Byers
Boston University
,
Ramesh Govindan
USC

Copyright © 2016 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

SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
SIGCOMM: ACM Special Interest Group on Data Communication
USENIX Assoc: USENIX Assoc

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 November 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

IMC 2016

Sponsor:

SIGMETRICS
SIGCOMM
USENIX Assoc

IMC 2016: Internet Measurement Conference

November 14 - 16, 2016

California, Santa Monica, USA

Acceptance Rates

IMC '16 Paper Acceptance Rate 48 of 184 submissions, 26%;

Overall Acceptance Rate 277 of 1,083 submissions, 26%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

20
Total Citations
View Citations
479
Total Downloads

Downloads (Last 12 months)17
Downloads (Last 6 weeks)3

Reflects downloads up to 07 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Mishra SZanella AMartínez-Durive OMadariaga DZiemlicki CFiore M(2024)Characterizing 5G Adoption and its Impact on Network Traffic and Mobile Service ConsumptionIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621344(1531-1540)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621344
Zheng JLi ZQiu YLin HXiao HLi YLiu Y(2022)WebAssembly-based Delta Sync for Cloud Storage ServicesACM Transactions on Storage10.1145/350284718:3(1-31)Online publication date: 21-Sep-2022
https://dl.acm.org/doi/10.1145/3502847
Ando RKadobayashi YTakakura H(2021)Choice of parallelism: multi-GPU driven pipeline for huge academic backbone networkInternational Journal of Parallel, Emergent and Distributed Systems10.1080/17445760.2021.194100936:6(609-622)Online publication date: 24-Jun-2021
https://doi.org/10.1080/17445760.2021.1941009
Li JLi ZTyson GXie G(2020)Characterising Usage Patterns and Privacy Risks of a Home Security Camera ServiceIEEE Transactions on Mobile Computing10.1109/TMC.2020.3039787(1-1)Online publication date: 2020
https://doi.org/10.1109/TMC.2020.3039787
Marquez CGramaglia MFiore MBanchs ASmoreda Z(2020)Identifying Common Periodicities in Mobile Service Demands with Spectral Analysis2020 Mediterranean Communication and Computer Networking Conference (MedComNet)10.1109/MedComNet49392.2020.9191477(1-8)Online publication date: Jun-2020
https://doi.org/10.1109/MedComNet49392.2020.9191477
Zhou PWang YLi ZWang XTyson GXie G(2020)LogSayer: Log Pattern-driven Cloud Component Anomaly Diagnosis with Machine Learning2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)10.1109/IWQoS49365.2020.9212954(1-10)Online publication date: Jun-2020
https://doi.org/10.1109/IWQoS49365.2020.9212954
Fan XXiang CGong LHe XChen CHuang X(2019)UrbanEdgeProceedings of the ACM Turing Celebration Conference - China10.1145/3321408.3323089(1-6)Online publication date: 17-May-2019
https://dl.acm.org/doi/10.1145/3321408.3323089
Singh RFiore MMarina MTarable ANordio A(2019)Urban Vibes and Rural Charms: Analysis of Geographic Diversity in Mobile Service Usage at National ScaleThe World Wide Web Conference10.1145/3308558.3313628(1724-1734)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308558.3313628
Zhou JLi ZWu QSteenkiste PUhlig SLi JXie G(2019)TCP Stalls at the Server SideIEEE/ACM Transactions on Networking10.1109/TNET.2018.288628227:1(272-287)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1109/TNET.2018.2886282
Li JWang ZLi Z(2019)Understanding the Usage Characteristics of Personalized Online Video ServicesIEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)10.1109/INFCOMW.2019.8845313(786-791)Online publication date: Apr-2019
https://doi.org/10.1109/INFCOMW.2019.8845313
Show More Cited By

View Options

Get Access

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