Grants and Contributions:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

The Internet of Things connects billions of devices that collect, store, and analyze data about our environment, business and industrial processes, health and activities, and our society. Developing and deploying these devices is a multi-billion dollar industry, and there is a wide diversity of the technologies used and their capabilities. Typically, these devices have very limited hardware resources, and developing software for them is highly customized, time-consuming, and error-prone as software is developed specifically for each hardware platform and application use case.

The objective is to research techniques to dramatically reduce the cost and time to develop data collection software for embedded devices and implement and deploy these techniques as open source software for the worldwide community to use. A secondary objective is to deploy and evaluate the data collection systems in industrial and environmental monitoring applications and collaborate with researchers in these domains where the data analysis is critical.

The scientific approach is to investigate and evaluate data management techniques that are specifically designed for low-resource, low-power embedded devices that optimize their behavior for hardware limitations and unique features of flash memory. Our previous work has developed LittleD, the smallest, SQL relational database for embedded devices, that runs on as little as 4 KB of memory, IonDB, a key-value store for embedded devices, and novel optimized file systems and overwriting techniques for NOR flash. These technologies and contributions will be fully integrated and expanded to produce the smallest, most energy-efficient database for embedded devices with between 1 and 100 KB of memory and less than 256 KB for code space. There are no systems currently available in this space with the smallest database, SQLite, being too large for these devices. Our goal is for IonDB to be the ubiquitous, open source system for embedded devices like SQLite is for cell phones.

The significance of the research is that it addresses a pressing industrial need for databases to work on embedded devices where there is no current system available. The system will make it more efficient to develop and deploy embedded devices. Our research group will continue to work with partners such as the City of Kelowna and vineyards on applications of the system for irrigation management and environmental sustainability as well as other applications in environmental, health, and industrial data collection.