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Sazgar IoT: A Device-Centric IoT Framework and Approximation Technique for Efficient and Scalable IoT Data Processing
Ali Yavari1,2, Harindu Korala3, Dimitrios Georgakopoulos2
16G Research and Innovation Lab, Swinburne University of Technology, Melbourne, VIC 3122, Australia.
Sensors (Basel, Switzerland)
|June 10, 2023
Summary
Sazgar IoT processes data directly on Internet of Things (IoT) devices, eliminating network delays and high costs for time-sensitive applications. This novel framework ensures timely and accurate data analysis using on-device computation and approximation techniques.
Area of Science:
- Computer Science
- Data Science
- Internet of Things
Background:
- Cloud and edge-based Internet of Things (IoT) data analysis face network delays and high costs.
- These issues negatively impact time-sensitive IoT applications.
Purpose of the Study:
- Propose Sazgar IoT, a novel framework to address challenges in time-sensitive IoT data analysis.
- Leverage on-device IoT computing resources and approximation techniques to meet application time-bounds.
Main Methods:
- Utilize onboard computing resources of IoT devices for data analysis tasks.
- Employ approximation techniques for data analysis to meet time-bound and accuracy requirements.
- Optimize processing based on available computing resources.
Main Results:
- Sazgar IoT successfully met time-bound and accuracy requirements for a COVID-19 citizen compliance monitoring application.
- Experimental validation confirmed the framework's efficiency and scalability.
- Demonstrated significant cost reduction compared to cloud and edge computing solutions.
Conclusions:
- Sazgar IoT provides an efficient and scalable solution for time-sensitive IoT data processing.
- The framework effectively mitigates network delays and reduces costs associated with cloud/edge infrastructure.
- Sazgar IoT is a viable approach for real-time IoT applications requiring high performance and cost-effectiveness.
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