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RT-IFTTT: Real-Time IoT Framework with Trigger Condition-aware Flexible Polling Intervals [abstract]
Seonyeong Heo, Seungbin Song, Jong Kim, and Hanjun Kim
To Appear: Proceedings of the IEEE Real-time Systems Symposium (RTSS), December 2017.

With a simple "If This Then That" syntax, IoT frameworks such as IFTTT and Microsoft Flow allow users to easily create custom applets integrating sensors and actuators. Since users expect their applets to respond to changed sensor values within a certain latency while the sensors usually have limited battery power, reading the sensor values at the right time point is crucial for the IoT frameworks to support real- time responses of the applets while maximizing battery lives of sensors. However, existing IoT frameworks periodically read the sensor data with fixed intervals without reflecting current sensor values and trigger conditions of applets, so the intervals are either too long to meet the real-time constraints, or too short wasting batteries of sensors. This work extends the existing IFTTT syntax for users to describe real-time constraints, and proposes the first real-time IoT framework with trigger condition-aware flexible polling intervals, called RT-IFTTT. RT-IFTTT analyzes current sensor values, trigger conditions and constraints of all the applets in the framework, and dynamically calculates the optimal polling intervals for each sensor. This work collects real-world sensing data from 10 physical sensors for 10 days, and shows that the RT-IFTTT framework with the proposed schedulers executes 100 to 400 applets according to user-defined real-time constraints with up to 64.01% less sensor polling counts compared to the framework with the fixed intervals.