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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Florida |
| Country | United States |
| Start Date | Jul 15, 2021 |
| End Date | Dec 31, 2022 |
| Duration | 534 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2134548 |
The broader impact/commercial potential of this I-Corps project is to enable and support the emerging class of Internet-of-Things (IoT) applications by delivering a scalable, self-organizing, self-healing, virtual private network connecting devices spanning from the cloud to the network's edge. Edge computing encompasses a growing set of technologies that enable data storage and processing within geographic proximity of sensors and IoT devices.
This technology provides a foundation of low-latency response times and high-throughput data access for a wide range of emerging applications, such as smart cities, manufacturing, defense, remote sensing/monitoring/analytics, advertising, and entertainment. Specifically, this project will advance technologies that have the potential to lower the cost of development, deployment, and management of edge computing applications by enabling existing applications to communicate without modifications, across a geographically dispersed set of heterogeneous edge computing resources residing on multiple providers.
These capabilities are envisioned to be of direct benefit to system integrators and/or application developers who build products that can incorporate and utilize the service as part of their respective solutions.
This I-Corps project pursues commercialization of a network virtualization technology for edge computing that builds on the research and development of a self-managing and self-organizing software-defined overlay network. The system assembles its base abstraction (a data-plane of Internet tunnels organized as a structured peer-to-peer overlay topology) and then autonomously routes virtual network traffic in a manner that is transparent to applications.
Its decentralized approach has been shown to be flexible, scalable, and resilient to failures. Internet-of-Things (IoT) class applications or cyber-physical solutions exhibit workflows that depend heavily on Internet Protocol (IP) based communications among devices and applications that are distributed across multiple geographic sites. These environments will typically incorporate large numbers of heterogeneous devices that have complex, evolving network configurations that are challenging and error-prone to manually administer - challenges which are directly addressed by this project at the network layer.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
University of Florida
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