
NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
Recipient: |
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Initial Amendment Date: | September 9, 2014 |
Latest Amendment Date: | August 22, 2018 |
Award Number: | 1440745 |
Award Instrument: | Standard Grant |
Program Manager: |
Kevin Thompson
kthompso@nsf.gov (703)292-4220 OAC Office of Advanced Cyberinfrastructure (OAC) CSE Directorate for Computer and Information Science and Engineering |
Start Date: | October 1, 2014 |
End Date: | September 30, 2019 (Estimated) |
Total Intended Award Amount: | $788,605.00 |
Total Awarded Amount to Date: | $788,605.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
150 MUNSON ST NEW HAVEN CT US 06511-3572 (203)785-4689 |
Sponsor Congressional District: |
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Primary Place of Performance: |
AKWatson Hall New Haven CT US 06520-8285 |
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): | Information Technology Researc |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.070 |
ABSTRACT
Intelligent management of campus research networks has become a major challenge for many institutions, as their networks grow rapidly in size and complexity in order to meet the demands of on-campus scientists who are conducting research, collaborating with peers, and fulfilling their mission of scientific education. Traditional, static network management approaches are no longer adequate, since they often result in low efficiency, poor usability, and unpredictable network application performance.
The goal of this project is to design and deploy a novel intelligent network cyberinfrastructure that greatly expands the ability of scientists to rapidly and efficiently move the large quantities of data required for computation- and data-intensive scientific workflows. To ensure a broad impact, the project includes specific focus on a range of science drivers in diverse fields such as astronomy, climatology, and genomics.
The project achieves its goal by leveraging and validating several prior networking research and development efforts. These include Maple, a novel Software Defined Networking (SDN) programming framework developed at Yale, and an Application Layer Traffic Optimization (ALTO) protocol and framework pioneered at Yale and now incorporated in a proposed standard for the Internet by the Internet Engineering Task Force. Maple simplifies network programming for end-to-end, complex, dynamically constructed network services, while ALTO enables network applications to adapt dynamically, according to network states, to deliver network efficiency and application quality of service. In addition, the project builds on prior Yale and NSF investments in high-speed physical network cyberinfrastructure, the widely-adopted InCommon authentication framework, and IPv6 technology.
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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.
This project (CC*IIE Integration: Dynamically Optimizing Research Data Workflow with a Software Defined Science Network, Award# 1440745) develops a programmable, efficient network cyberinfrastructure (CI) at Yale to support scientists both at Yale and broadly to greatly expand the ability of scientists to rapidly and efficiently move the large quantities of data required for complex computation- and data-intensive scientific workflows. A network infrastructure based on traditional designs can be too too inefficient and static (e.g., multiple, static, redundant networks) to support such workflows.
The intellectual foundation of the project is two successful research innovations at Yale: (1) Maple, which is a novel, high-level network programming framework to introduce programmability into network management. By changing a network from static to programmable, the network gains an essential ability to introduce end-to-end, complex, dynamically constructed network services. (2) Application-layer traffic optimization (ALTO), which is a Proposed Standard of the Internet to integrate network traffic optimization and application-layer traffic optimization. Since the flexibility and efficiency of an infrastructure depends on both the resource provider (network) and the resource consumer (applications), by introducing ALTO, the infrastructure can achieve flexibility and efficiency which cannot be achieved by either network or applications alone.
The project makes significant intellectual progress in realizing the design beyond the initial foundation. (1) It extends the state-of-art programmable networking from single domain (i.e., one network) to multi-domain, geo-distributed software-defined networking to better support key science drivers (e.g., LHC), which consist of multiple organizations, where each organization has its own network (domain) and its local policies to limit complete programmability. (2) It introduces systematic foundations to understand the capabilities of existing framework (e.g., a learning based BoxOpt framework on the feasibility of using existing networking resource models) and the fundamental limitation of any programmable networking (e.g., a network programming capacity theorem). (3) It introduces fundamental primitives to handle challenges including handling complex dynamicity (e.g., the Update Algebra and the Trident uniform, consistent programming model), predicting resource availability (e.g., a model based Prophet model, and a secure multi-party computation based on multi-domain resource aggregation model), and introducing reliability (i.e., the novel multi-control-plane architecture).
The project also devote substantial efforts to achieve broader impacts. In particular, the key goal of the project is to demonstrate the benefits of a single, flexible network and the benefits have motivated Yale to deploy related techniques on the whole Yale network, achieving a major outcome of this project. The project works closely with the LHC/CMS science driver collaborators, and demonstrated the benefits of the systems at multiple settings including substantial demos at SuperComputing. The project also leads to substantial progress in the design and implementation of the ALTO Internet standards, which has proven extremely valuable for broader impacts. In particular, ALTO was the foundational framework for a large-scale deployment between one of the largest eyeball networks and a leading hyper-giant (paper see http://people.csail.mit.edu/gsmaragd/publications/CoNEXT2019/; a succint summary of impact of ALTO see slide 36 of http://people.csail.mit.edu/gsmaragd/publications/CoNEXT2019/CoNEXT2019-presentation.pdf). The project adopts a open-source, public-domain policy, and makes all of your systems publicly available.
Last Modified: 01/10/2020
Modified by: Yang R Yang
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