Award Abstract # 0820944
SGER: Exploratory Research on End-User Opt-In and Broadening Research Engagement

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: RTX BBN TECHNOLOGIES, INC.
Initial Amendment Date: February 29, 2008
Latest Amendment Date: January 29, 2010
Award Number: 0820944
Award Instrument: Standard Grant
Program Manager: C. Iacono
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: February 15, 2008
End Date: July 31, 2010 (Estimated)
Total Intended Award Amount: $0.00
Total Awarded Amount to Date: $199,998.00
Funds Obligated to Date: FY 2008 = $199,998.00
History of Investigator:
  • Brig 'Chip' Elliott (Principal Investigator)
    celliott@bbn.com
Recipient Sponsored Research Office: Raytheon BBN Technologies Corp.
10 MOULTON ST
CAMBRIDGE
MA  US  02138-1119
(617)873-8325
Sponsor Congressional District: 05
Primary Place of Performance: Raytheon BBN Technologies Corp.
10 MOULTON ST
CAMBRIDGE
MA  US  02138-1119
Primary Place of Performance
Congressional District:
05
Unique Entity Identifier (UEI): JAXJSTJJSP74
Parent UEI: EGAVSJTA2D81
NSF Program(s): NetS RESEARCH RESOURCES
Primary Program Source: 01000809DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9218, 9237, HPCC
Program Element Code(s): 791700
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

In this SGER, BBN is proposing to engage in preliminary work on two untested and novel ideas. The first idea focuses on the challenge of how to generate and support realistic traffic flow on experimental, network infrastructure. Other network infrastructure typically relies on artificial traffic generation methods or user communities that are composed of the experimenters themselves. But, in order to provide experimenters with real traffic at scale, novel approaches and mechanisms need to be developed. If such mechanisms can be developed and real traffic is carried on the infrastructure, many hard problems remain. For example, how many and what types of opt-in mechanisms are actually needed? Will the infrastructure have enough ?user pull? (e.g., applications, capabilities, etc.) to attract users? What kind of guarantees can be given to the users ? in terms of privacy, reliability, security, etc? These questions can not currently be answered as new interdisciplinary knowledge needs to be generated. This SGER will allow for the development of a series of white papers on this topic, including 1) strategies to encourage opt-in, 2) applications that could drive user opt-in, 3) legal, ethical, privacy and security implications of user opt-in, 4) prospective user communities and methods for accessing them, and 5) the potential benefits of user opt-in for the commercial sector. The authors of these papers will meet at the Engineering Conferences to discuss and share their findings and how they might be implemented in an experimental network infrastructure.

The second novel idea revolves around broadening research engagement and interest in network infrastructure. It is essential that the widest range of scientists and engineers with research interests beyond networking and distributed systems be allowed to carry out their own experiments on novel, network infrastructure. Other disciplines that might be interested include the social sciences, economics, business, law, medicine, and alternative energy, for example. Such a broad purview helps to ensure that new network infrastructure will widely influence research and education. But it is essential that their requirements for experimental workflow, data access and measurement, for example, be generated now so that they can influence infrastructure design. If those requirements are not known early, some areas of science may be locked out from use of the infrastructure. It is critical that experts be engaged now to generate those requirements. This SGER will help to generate infrastructure requirements for network researchers in the social sciences, law, economics, and other disciplines interested in network science and engineering, which will allow for new network infrastructure to have the broadest possible impacts.

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