Title
RT-IFTTT: Real-Time IoT Framework with Trigger Condition-Aware Flexible Polling Intervals
Abstract
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. Users expect appropriate actions to be taken within a certain latency in response to sensor value changes while the sensors usually have limited battery power. Therefore, reading the sensor values at the right time point is crucial for the IoT frameworks to support real-time responses of the applets while saving 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 efficient 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 scheduling algorithm executes 100 to 400 applets according to user-defined real-time constraints with up to 64.12% less sensor polling counts compared to the framework with the fixed intervals.
Year
DOI
Venue
2017
10.1109/RTSS.2017.00032
2017 IEEE Real-Time Systems Symposium (RTSS)
Keywords
Field
DocType
Internet-of-Things,Real-time-systems,Scheduling-algorithms,Event-detection
Time point,Latency (engineering),Computer science,Scheduling (computing),Internet of Things,Polling,Real-time computing,Current sensor,Battery (electricity),Actuator
Conference
ISSN
ISBN
Citations 
1052-8725
978-1-5386-1416-7
2
PageRank 
References 
Authors
0.37
0
4
Name
Order
Citations
PageRank
Seonyeong Heo1183.67
Seungbin Song232.06
Jong Uk Kim3595.56
Hanjun Kim410811.11