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Research Spending & Results

Award Detail

Doing Business As Name:University of Delaware
  • Rui Zhang
  • (302) 831-2711
Award Date:09/13/2019
Estimated Total Award Amount: $ 250,000
Funds Obligated to Date: $ 250,000
  • FY 2019=$250,000
Start Date:11/01/2019
End Date:10/31/2022
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:SaTC: CORE: Small: Collaborative: Trustworthy Hierarchical Edge Computing
Federal Award ID Number:1933047
DUNS ID:059007500
Parent DUNS ID:059007500
Program:Secure &Trustworthy Cyberspace
Program Officer:
  • Alexander Sprintson
  • (703) 292-2170

Awardee Location

Street:210 Hullihen Hall
Awardee Cong. District:00

Primary Place of Performance

Organization Name:University of Delaware
Street:210 Hullihen Hall
Cong. District:00

Abstract at Time of Award

Edge computing has quickly risen as an effective paradigm to capture, process, gain insights from, and act upon the massive amount of Internet of Things (IoT) data close to where it is generated. Future edge computing systems are expected to be hierarchical and heterogeneous. It will become increasingly common for a single IoT application to utilize edge computing resources owned by multiple entities. This project envisions the emergence of hierarchical edge computing (HEC) service providers that purchase computing services from heterogeneous multi-owner edge computing systems and provide unified edge computing services to individual IoT applications. The development of HEC systems will have a profound impact on transportation, healthcare, energy, education, social life, public safety, and many other sectors. Security and privacy are among the most challenging obstacles that hinder the wide development and deployment of the promising HEC paradigm. This project aims to tackle key security and privacy challenges in HEC systems, under which heterogeneous multi-owner edge computing systems can jointly provide trustworthy computing services to end-users via a single service provider. There are four research thrusts: (1) developing novel techniques to authenticate data streams with freshness guarantees; (2) investigating locally differentially private data analysis techniques via correlated randomized responses; (3) designing a novel framework for distributed privacy-preserving collaborative learning; and (4) building a prototype HEC system to thoroughly validate and evaluate the proposed techniques. If successful, the research can serve as a key enabler for the explosive development and deployment of edge computing services and IoT applications. The research will also enrich the scientific knowledge of network and distributed system security, data privacy, and edge computing. A substantial quantity of project deliverables will be made publicly available online through tutorials, talks, publications, and software toolkits. In addition, this project will integrate the research activities with curriculum development, provide research opportunities to female and underrepresented students, enhance undergraduate research experience through senior design projects, and foster the interest of K-12 students in science, technology, engineering, and math (STEM) via outreach programs. 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.

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