Automatic Generation of IoT Device Platforms With AutoLink

With the development of the Internet-of-Things (IoT) industry, developers are no longer content with just prototyping a valid system but eager to create a mature IoT system that explores low power consumption or high extensibility instead. In this article, we present AutoLink, an automatic generatio...

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Bibliographic Details
Published in:IEEE internet of things journal 2021-04, Vol.8 (7), p.5893-5903
Main Authors: Li, Borui, Dong, Wei
Format: Article
Language:English
Subjects:
Batteries
Configurations
Energy
Estimation
Extensibility
Hardware
Industrial development
Internet of Things
Internet of Things (IoT)
Optimization
Platforms
Power consumption
Power management
Prototyping
rapid break development
Sensors
Syntactics
User requirements
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Description
Summary:With the development of the Internet-of-Things (IoT) industry, developers are no longer content with just prototyping a valid system but eager to create a mature IoT system that explores low power consumption or high extensibility instead. In this article, we present AutoLink, an automatic generation system of IoT device platforms. Users may write AutoLink metaprogram with an expressive syntax to specify their diverse requirements (e.g., battery lifetime, interface extensibility, execution time, and cost) of the generated IoT device platform. Taking the metaprogram as an input, AutoLink automatically transforms it into corresponding optimization problems and generates the optimal hardware configuration that meets user requirements best. Toward this, AutoLink also offers a cross-platform, duty cycle-aware power model and a time model to estimate the lifetime and execution period of an IoT system. We implement AutoLink and evaluate its performance using real-world IoT applications. Results show that AutoLink generates the optimal hardware configuration that meets diverse user requirements. Moreover, AutoLink achieves superior power estimation accuracy of IoT device platforms compared with the state-of-the-art approach.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2020.3033130