| NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
| Recipient: |
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| Initial Amendment Date: | September 13, 2012 |
| Latest Amendment Date: | January 29, 2015 |
| Award Number: | 1246133 |
| 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: | January 1, 2013 |
| End Date: | December 31, 2015 (Estimated) |
| Total Intended Award Amount: | $800,000.00 |
| Total Awarded Amount to Date: | $800,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1200 E CALIFORNIA BLVD PASADENA CA US 91125-0001 (626)395-6219 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1200 E California Blvd MC256-48 Pasadena CA US 91125-0001 |
| 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): | Campus Cyberinfrastructure |
| 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
Recent years have seen a dramatic evolution in the area of research and education networking, enabling faster data rates and novel services to user communities. The ANSE project integrates these new services, in particular dynamic bandwidth allocation (DYNES) and real-time network performance monitoring (perfSONAR), with the higher level workload management software deployed for the Large Hadron Collider (LHC), like PanDA and PhEDEx in the ATLAS and CMS experiments, respectively. A software defined networking approach, and in particular the use of dynamic bandwidth allocation capability, already available in ESnet and Internet2 networks, makes the network a truly manageable resource, on par with computing (CPU) and storage (disk and tape) resources. This approach enables smart optimization of resource utilization through co-scheduling and deadline scheduling algorithms within data and workload management systems. The ANSE system reacts to real-time conditions such as network events or node failure, as well as usage specific parameters like changes in data distribution priorities. Importance is given to the multi-domain aspects of networking, as required for a globally distributed system.
While the primary target for ANSE is the LHC experiments, the ANSE project is clearly applicable to other data intensive science fields as well. Through the use of recognized standards such as the OGF NSI, ANSE is applicable beyond the use case of the LHC, and in particular to all distributed computing and data intensive applications of global scale.
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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.
Highly capable and reliable networks have been critical to the science discoveries in high energy physics for the last decades, and this has been increasingly true in other data intensive fields ranging from astrophysics and photon science to genomics in recent years. As the needs of the leading programs for acquiring, processing, distributing and analyzing globally distributed data have continued to grow exponentially in both scale and complexity, the science programs and the world’s research and education networks that support them have been increasingly challenged. A new class of agile software driven systems coordinating network, storage and computing resources worldwide is required if these programs are to continue to realize their full potential for discoveries, now and in the coming decade.
The ANSE (Advanced Network Services for Experiments) project, which began on January 1, 2013 and completed in the Fall of 2015, has had a pivotal role in meeting these challenges, leaving behind a strong legacy and a path forward in terms of integrating advanced network methods and services into the mainstream operations and systems of major data intensive science programs, starting with the CMS and ATLAS experiments at the LHC. The outcomes of ANSE have paved the way towards more effective and coordinated use of the world’s research and education networks by these experiments, by other upcoming data intensive programs with needs on a similar scale such as the Large Synoptic Space Telescope (LSST), and by future programs with even greater needs such as the High Luminosity LHC (HL LHC), the Square Kilometer Array (SKA) and several projects in genomics which foresee exabyte-scale and larger datasets.
The rise of Software Defined Networks (SDN) before and during the ANSE project enabled the team to make rapid progress in meeting its goals, while making leading edge contributions to the concept and development of SDN systems of global scope. By exploiting and contributing to this trend in the research community and industry, the ANSE team and its science, network and industry partners developed and deployed the first prototypes of a terabit/sec scale, software-driven dynamic system capable of provisioning and intelligently directing data flows, and coordinating the use of networks and storage on an unprecedented scale. This was demonstrated at the Supercomputing 2013-2015 conferences, in dedicated exercises among the US, Europe and Latin America aimed at the LSST program, and in a persistent testbed deployed in 2015 and now in operation at Caltech, the Starlight facility in Chicago, along with CERN, Fermilab, Michigan, as well as several campuses in the Pacific Research Platform.
The groundbreaking progress achieved in the ANSE project was accomplished through the development and integration of several technologies, pushing forward the state of the art in many cases, including:
(1) The ability to allocate guaranteed bandwidth across complex networks of global extent, notably including the LHC Open Network Environment (LHCONE), using both well-established and emerging standard (NSI) methods developed by the Energy Sciences network (ESnet) and partners in the Open Grid Forum,
(2) The ability to construct paths supporting the dynamic circuits and other classes of flows intelligently, taking into account the available bandwidth, profiles and priorities of various transfers, as well as the network state and performance on each segment, using a Software Defined Network (SDN) controller developed by the Caltech team,
(3) Coupling the path selection and flow management methods of the Caltech controller with end-site services based on Open vSwitch (OVS) to provide stable protocol agnost...
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