This program has been archived.
Division of Computer and Network Systems
NSF/VMware Partnership on Edge Computing Data Infrastructure (ECDI)
|Darleen L. Fisherfirstname.lastname@example.org||(703) 292-8950|
|Jack Brassilemail@example.com||(703) 292-8950|
|Samee Khanfirstname.lastname@example.org||(703) 292-8061|
|Mimi McClureemail@example.com||(703) 292-5197|
|J. Christopher Rammingfirstname.lastname@example.org||(650) 427-5000|
|David Ottemail@example.com||(650) 427-5816|
|Sujata Banerjeefirstname.lastname@example.org||(650) 427-1066|
Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 19-1), is effective for proposals submitted, or due, on or after February 25, 2019. Please be advised that, depending on the specified due date, the guidelines contained in NSF 19-1 may apply to proposals submitted in response to this funding opportunity.
The proliferation of mobile and Internet-of-Things (IoT) devices, and their pervasiveness across nearly every sphere of our society, continues to raise questions about the architectures that organize tomorrow’s compute infrastructure. At the heart of this trend is the data that will be generated as myriad devices and application services operate simultaneously to digitize a complex domain like a smart building or smart industrial facility. A key shift is from edge devices consuming data produced in the cloud to edge devices being a voluminous producer of data. This shift reopens a broad variety of system-level research questions concerning data placement, movement, processing and sharing. Importantly, the shift also opens the door to compelling new applications with significant industrial and societal impact in domains such as healthcare, manufacturing, transportation, public safety, energy, buildings, and telecommunications.
Edge computing is broadly defined as a networked systems architectural approach in which compute and storage resources are placed at the network edge, in proximity to the mobile and IoT devices. The approach offers advantages, such as improved scalability as local computation reduces the volume of data transported, reduced network latency and faster compute response times as data is processed on local compute nodes, and arguably improved security and privacy where data requirements preclude access and exchanges beyond the edge. Edge computing infrastructure may consist of IoT gateways, telephone central offices, cloudlets, micro data centers, or any number of schemes that support the provisioning of communication, compute and storage resources near edge devices.
This solicitation seeks to advance the state of the art in end-to-end networked systems architecture that includes edge infrastructures. The central challenge is to design and develop data-centric edge architectures, programming paradigms, runtime environments, and data sharing frameworks that will enable compelling new applications and fully realize the opportunity of big data in tomorrow’s mobile and IoT device environments. Researchers are expected to carefully consider the implications of edge computing’s multi-stakeholder context, and the need for security and privacy as first order design and operational considerations.