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.
|Original language||English (US)|
|Title of host publication||IMC 2017 - Proceedings of the 2017 Internet Measurement Conference|
|Publisher||Association for Computing Machinery|
|Number of pages||7|
|State||Published - Nov 1 2017|
|Event||2017 ACM Internet Measurement Conference, IMC 2017 - London, United Kingdom|
Duration: Nov 1 2017 → Nov 3 2017
|Name||Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC|
|Other||2017 ACM Internet Measurement Conference, IMC 2017|
|Period||11/1/17 → 11/3/17|
Bibliographical noteFunding Information:
We would like to thank our shepherd, Hamed Haddadi, and the anonymous reviewers for their valuable comments and suggestions. This research was supported in part by the National Science Foundation under grant #1629347 and #1566331.
© 2017 Association for Computing Machinery.