| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | August 28, 2018 |
| Latest Amendment Date: | August 28, 2018 |
| Award Number: | 1836870 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Deepankar Medhi
dmedhi@nsf.gov (703)292-2935 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2018 |
| End Date: | September 30, 2019 (Estimated) |
| Total Intended Award Amount: | $100,000.00 |
| Total Awarded Amount to Date: | $100,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
910 WEST FRANKLIN ST RICHMOND VA US 23284-9005 (804)828-6772 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
P.O. Box 980568 RICHMOND VA US 23298-0568 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Special Projects - CNS |
| Primary Program Source: |
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| Program Reference Code(s): | |
| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
The significant growth and penetration of smart and Internet of Things (IoT) devices has driven a large number of new applications and caused a surge in sensitive and personal data generation. Unfortunately, our ability to protect that information is limited, and concerns over privacy, trust, and security are becoming increasingly important to different stakeholders. Emerging IoT applications also send and receive data in various ways, and each might require different performance levels of reliability, loss, and latency. To cope with these various traffic characteristics and requirements, it is now necessary to have greater visibility and control over the traffic generated from smart and IoT devices in order to guarantee a high quality of experience to users.
The aim of this project is to design and develop the ExtremeDataHub platform, an open, flexible, and programmable networked edge device that controls and manages access to our sensitive and personal data. This platform will integrate the European collaborators' SMILE and Databox platforms. The project will identify new services and applications that can effectively leverage the combined platform, potentially including applications in the smart home, smart healthcare, and smart cities domains. This project initiates a new research collaboration between investigators at Virginia Commonwealth University and Imperial College London, UK.
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The significant growth and penetration of smart and IoT devices come along with a tremendous increase in the number of smart and IoT applications. These various applications, which support various domains and services, generate and access different data patterns such as periodic, event-based, realtime and continuous data. To cope with these various traffic characteristics that require different performance levels of reliability, loss, and latency, it is now necessary to have greater visibility and control over the traffic generated from smart and IoT devices in order to guarantee an optimized performance of smart and IoT applications as well as high quality of experience to users.
The project, as research collaboration initiation between US and Europe (including UK), aimed at designing and developing ExtremeDataHub platform; an open-source, flexible, and programmable networked edge device that collates and mediates access to our sensitive and personal data, under the data subjects control as well as to cope with various characteristics and requirements of smart and IoT applications that access this data in order to provide better performance and quality of experience to users. More specifically, this research-initiation project's activities included 1) Design and development of ExtremeDataHub integrated platform as a networked edge device that enables individuals to control and manages their sensitive and personal data as well as to provide flexibility and controllability to support various characteristics and requirements of different data access flows generated by smart and IoT applications. This integrated platform will leverage a platform previously developed by US PI and another platform developed by the UK collaborator. 2) Identify and explore interesting new services and applications of ExtremeDataHub in several of smart environments. One interesting services we developed as a proof-of-concept use-case for ExtremeDataHub is HomeMon. HomeMon is a smart home service that enables video streaming differentiation service based on the feed priorities that guarantee a certain quality for the high priority video feeds. 3) Form the team, explore industrial collaboration, and prepare for large proposals.
This project facilitated the research collaboration by funding several members from US research group to travel and meet members from the UK research group. The project also carried out a number of educational activities involving recruiting and mentoring under-represented students, and enriching undergraduate and graduate curricula. This project used to fund several graduate students (Ph.D. students) in the fields of wireless networking, data privacy and edge computing. The project also used to support minorities since one of the PhD students is a female student. Research and findings of this project were incorporated into the PI's graduate course (CMSC 623 - Cloud Computing) as an example of edge computing services. In addition, we used this project to outreach to high school students and expose them to data privacy and edge computing aspects. Moreover, this project helped the PI to establish a collaboration with industry on the design and development of privacy framework for IoT devices.
Last Modified: 01/31/2020
Modified by: Tamer Nadeem
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