research-article

An empirical characterization of IFTTT: ecosystem, usage, and performance

Authors:

XiaoFeng WangAuthors Info & Claims

IMC '17: Proceedings of the 2017 Internet Measurement Conference

Pages 398 - 404

https://doi.org/10.1145/3131365.3131369

Published: 01 November 2017 Publication History

Abstract

IFTTT is a popular trigger-action programming platform whose applets can automate more than 400 services of IoT devices and web applications. We conduct an empirical study of IFTTT using a combined approach of analyzing data collected for 6 months and performing controlled experiments using a custom testbed. We profile the interactions among different entities, measure how applets are used by end users, and test the performance of applet execution. Overall we observe the fast growth of the IFTTT ecosystem and its increasing usage for automating IoT-related tasks, which correspond to 52% of all services and 16% of the applet usage. We also observe several performance inefficiencies and identify their causes.

References

[1]

Amazon echo - what we know now (updated). http://files.constantcontact.com/150f9af2201/70c07fdd-a197-4505-9476-e83aa726f025.pdf.

[2]

Atooma. https://www.atooma.com/.

[3]

Google APIs. https://console.developers.google.com/.

[4]

IFTTT. https://ifttt.com/.

[5]

IFTTT API(2017). https://platform.ifttt.com/docs/api_reference.

[6]

IFTTT Egg Minder Service. https://ifttt.com/eggminder.

[7]

OAuth 2.0. https://oauth.net/2/.

[8]

Philips Hue. http://www2.meethue.com/en-us/.

[9]

Philips Hue API. https://www.developers.meethue.com/philips-hue-api.

[10]

Stringify. https://www.stringify.com/.

[11]

Tasker for Android. http://tasker.dinglisch.net/.

[12]

Turn on notifications in a Google spreadsheet. https://support.google.com/docs/answer/91588.

[13]

Waylay.io. http://www.waylay.io/index.html.

[14]

WigWag smart home. https://www.wigwag.com/home.html.

[15]

Zipato. https://www.zipato.com/.

[16]

F. Cabitza, D. Fogli, R. Lanzilotti, and A. Piccinno. End-user development in ambient intelligence: a user study. In Proceedings of the 11th Biannual Conference on Italian SIGCHI Chapter, pages 146--153. ACM, 2015.

Digital Library

[17]

L. De Russis and F. Corno. Homerules: A tangible end-user programming interface for smart homes. In Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, pages 2109--2114. ACM, 2015.

Digital Library

[18]

A. K. Dey, T. Sohn, S. Streng, and J. Kodama. icap: Interactive prototyping of context-aware applications. In International Conference on Pervasive Computing, pages 254--271. Springer, 2006.

Digital Library

[19]

J. Huang and M. Cakmak. Supporting mental model accuracy in trigger-action programming. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pages 215--225. ACM, 2015.

Digital Library

[20]

C.-J. M. Liang, B. F. Karlsson, N. D. Lane, F. Zhao, J. Zhang, Z. Pan, Z. Li, and Y. Yu. Sift: building an internet of safe things. In Proceedings of the 14th International Conference on Information Processing in Sensor Networks, pages 298--309. ACM, 2015.

Digital Library

[21]

S. Mennicken, J. Vermeulen, and E. M. Huang. From today's augmented houses to tomorrow's smart homes: new directions for home automation research. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pages 105--115. ACM, 2014.

Digital Library

[22]

A. A. Nacci, B. Balaji, P. Spoletini, R. Gupta, D. Sciuto, and Y. Agarwal. Buildingrules: a trigger-action based system to manage complex commercial buildings. In Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers, pages 381--384. ACM, 2015.

Digital Library

[23]

M. W. Newman, A. Elliott, and T. F. Smith. Providing an integrated user experience of networked media, devices, and services through end-user composition. In International Conference on Pervasive Computing, pages 213--227. Springer, 2008.

Digital Library

[24]

M. Z. Shafiq, L. Ji, A. X. Liu, J. Pang, and J. Wang. A first look at cellular machine-to-machine traffic: large scale measurement and characterization. ACM SIGMETRICS Performance Evaluation Review, 40(1):65--76, 2012.

Digital Library

[25]

M. Surbatovich, J. Aljuraidan, L. Bauer, A. Das, and L. Jia. Some recipes can do more than spoil your appetite: Analyzing the security and privacy risks of ifttt recipes. In Proceedings of the 26th International Conference on World Wide Web, pages 1501--1510. International World Wide Web Conferences Steering Committee, 2017.

Digital Library

[26]

K. Tada, S. Takahashi, and B. Shizuki. Smart home cards: tangible programming with paper cards. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, pages 381--384. ACM, 2016.

Digital Library

[27]

B. Ur, E. McManus, M. Pak Yong Ho, and M. L. Littman. Practical trigger-action programming in the smart home. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 803--812. ACM, 2014.

Digital Library

[28]

B. Ur, M. Pak Yong Ho, S. Brawner, J. Lee, S. Mennicken, N. Picard, D. Schulze, and M. L. Littman. Trigger-action programming in the wild: An analysis of 200,000 ifttt recipes. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pages 3227--3231. ACM, 2016.

Digital Library

[29]

M. Walch, M. Rietzler, J. Greim, F. Schaub, B. Wiedersheim, and M. Weber. homeblox: making home automation usable. In Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication, pages 295--298. ACM, 2013.

Digital Library

[30]

J.-b. Woo and Y.-k. Lim. User experience in do-it-yourself-style smart homes. In Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing, pages 779--790. ACM, 2015.

Digital Library

Cited By

Giudici MPadalino LPaolino GParatici IPascu AGarzotto F(2024)Designing Home Automation Routines Using an LLM-Based ChatbotDesigns10.3390/designs80300438:3(43)Online publication date: 13-May-2024
https://doi.org/10.3390/designs8030043
Zhao KZhang HLi JPan QLai LNie YZhang Z(2024)Clustering on heterogeneous IoT information network based on meta pathScience Progress10.1177/00368504241257389107:2Online publication date: 17-Jun-2024
https://doi.org/10.1177/00368504241257389
Deng BSun BShen L(2024)laTAPE: Location-Aware Programming and Executing Trigger-Action RulesProceedings of the 15th Asia-Pacific Symposium on Internetware10.1145/3671016.3672579(503-506)Online publication date: 24-Jul-2024
https://dl.acm.org/doi/10.1145/3671016.3672579
Show More Cited By

Index Terms

An empirical characterization of IFTTT: ecosystem, usage, and performance
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Embedded systems
2. Networks
  1. Network performance evaluation
  2. Network types
    1. Home networks

Recommendations

Automatic generation of IFTTT mashup infrastructures
ASE '20: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

In recent years, IF-This-Then-That (IFTTT) services are becoming more and more popular. Many platforms such as Zapier, IFTTT.com, and Workato provide such services, which allow users to create workflows with "triggers" and "actions" by using Web ...
A Graduate-Level Course on Entity Resolution and Information Quality: A Step toward ER Education
Special Issue on Entity Resolution

This article discusses the topics, approaches, and lessons learned in teaching a graduate-level course covering entity resolution (ER) and its relationship to information quality (IQ). The course surveys a broad spectrum of ER topics and activities ...
iThem: Programming Internet of Things Beyond Trigger-Action Pattern
UIST '22 Adjunct: Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology

With emerging technologies bringing Internet of Things (IoT) devices into domestic environments, trigger-action programming such as IFTTT with its simple if-this-then-that pattern provides an effective way for end-users to connect fragmented ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

IMC '17: Proceedings of the 2017 Internet Measurement Conference

November 2017

509 pages

ISBN:9781450351188

DOI:10.1145/3131365

General Chairs:
Steve Uhlig
Queen Mary University of London
,
Olaf Maennel
Tallinn University of Technology

Copyright © 2017 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

In-Cooperation

USENIX Assoc: USENIX Assoc

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

IMC '17

Sponsor:

IMC '17: Internet Measurement Conference

November 1 - 3, 2017

London, United Kingdom

Acceptance Rates

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

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

108
Total Citations
View Citations
894
Total Downloads

Downloads (Last 12 months)94
Downloads (Last 6 weeks)12

Reflects downloads up to 16 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Giudici MPadalino LPaolino GParatici IPascu AGarzotto F(2024)Designing Home Automation Routines Using an LLM-Based ChatbotDesigns10.3390/designs80300438:3(43)Online publication date: 13-May-2024
https://doi.org/10.3390/designs8030043
Zhao KZhang HLi JPan QLai LNie YZhang Z(2024)Clustering on heterogeneous IoT information network based on meta pathScience Progress10.1177/00368504241257389107:2Online publication date: 17-Jun-2024
https://doi.org/10.1177/00368504241257389
Deng BSun BShen L(2024)laTAPE: Location-Aware Programming and Executing Trigger-Action RulesProceedings of the 15th Asia-Pacific Symposium on Internetware10.1145/3671016.3672579(503-506)Online publication date: 24-Jul-2024
https://dl.acm.org/doi/10.1145/3671016.3672579
Wang LVincent NRukanskaitė JZhang A(2024)Pika: Empowering Non-Programmers to Author Executable Governance Policies in Online CommunitiesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642012(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642012
Wan LWang KWang HBai GChua TNgo CKa-Wei Lee RKumar RLauw H(2024)Is It Safe to Share Your Files? An Empirical Security Analysis of Google WorkspaceProceedings of the ACM Web Conference 202410.1145/3589334.3645697(1892-1901)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645697
Sun DHu LWu GXing YHu JWang F(2024)Threat Detection in Trigger-Action Programming Rules of Smart Home With Heterogeneous Information Network ModelIEEE Internet of Things Journal10.1109/JIOT.2024.336295011:10(18320-18334)Online publication date: 15-May-2024
https://doi.org/10.1109/JIOT.2024.3362950
Aghvamipanah MAmini MArtho CBalliu M(2024)Activity Recognition Protection for IoT Trigger-Action Platforms2024 IEEE 9th European Symposium on Security and Privacy (EuroS&P)10.1109/EuroSP60621.2024.00039(600-616)Online publication date: 8-Jul-2024
https://doi.org/10.1109/EuroSP60621.2024.00039
Fei YRendy BKumar RDartsi OSahasrabuddhe HMcDermott MWang ZSzymanski NWalters LMilsted DZeng YJain ACeder G(2024)AlabOS: a Python-based reconfigurable workflow management framework for autonomous laboratoriesDigital Discovery10.1039/D4DD00129JOnline publication date: 2024
https://doi.org/10.1039/D4DD00129J
Xing YHu LDu XShen ZHu JWang F(2024)A privacy-preserving federated graph learning framework for threat detection in IoT trigger-action programmingExpert Systems with Applications10.1016/j.eswa.2024.124724255(124724)Online publication date: Dec-2024
https://doi.org/10.1016/j.eswa.2024.124724
Wu GWang MWang F(2024)TAP with ease: a generic recommendation system for trigger-action programming based on multi-modal representation learningApplied Soft Computing10.1016/j.asoc.2024.112163166(112163)Online publication date: Nov-2024
https://doi.org/10.1016/j.asoc.2024.112163
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