perfSONAR is being used around the world; here are a few examples of projects that are solving problems quicker because of their pS deployments:
John Bigrow, Brookhaven National Laboratory (BNL) -- BNL, which serves as the US ATLAS Tier-1 facility, has incorporated the perfSONAR Performance Toolkit into its infrastructure to provide a network troubleshooting, performance, and trend analysis capability. BNL has both the European version of this toolkit, commonly referred to as MDM from our European collaborators, and the perfSONAR-PS (collaboratively created by the Internet2 and ESnet community) version as part of the US ATLAS working group. "These toolsets will provide a common framework for network performance and analysis for the Large Hadron Collider community to troubleshoot network related problems," states Bigrow, a Technology Architect at BNL supporting US ATLAS.
Jason Lee, DOE’s National Energy Research Scientific Computing Center (NERSC) -- In addition to detecting soft failures in networks transporting data from the LHC, perfSONAR has also been used to identify bottlenecks in networks connecting the upcoming Daya Bay Neutrino Experiment in Southern China to computing and mass storage systems at DOE’s NERSC in Oakland, California, where data from the experiment will be analyzed and archived. Neutrinos are subatomic particles that widely populate the universe. Scientists initially believed that these particles did not contain any mass, but recent evidence proved otherwise. The Daya Bay experiment hopes to gain insights into the mass of these particles by investigating the properties of neutrino oscillation, or the mixing of neutrinos. A better understanding of these puzzling particles could provide valuable insights into mysterious dark matter, the invisible material that makes up most of the cosmos.
“Before perfSONAR, it usually took several days to pinpoint the source of a bottleneck when massive datasets were transferred across multiple networks. We had to work with operators of each network to identify the problem and have it fixed,” says Lee, a NERSC network engineer. “Because perfSONAR actively and automatically searches for problems, we can quickly find choke points and immediately know who to contact to get it fixed.” (more)
Shawn McKee, University of Michigan -- One of the largest upcoming networking challenges for the high energy physics community is transferring and accessing large datasets related to experiments at the Large Hadron Collider (LHC) at CERN in Switzerland. Once the LHC goes into full production in late 2009, terabytes of data will flow from CERN to Brookhaven National Laboratory (BNL) in New York and Fermi National Accelerator Laboratory in Illinois, called Tier 1 U.S. LHC sites.
From Europe to the U.S. Tier 1 sites, the data will traverse two networks, USLHCnet and ESnet. The data will then be sent to five other centers, known as Tier 2 sites, in the U.S., from which physicists around the nation will be able to access and study the data. From the Tier 1 to Tier 2 sites, LHC data will traverse the ESnet and Internet2 backbones and various local area networks.
“If we don’t perform well, it slows everybody down, physicists want the data to arrive as fast as humanly possible, if not faster,” said Shawn McKee, a high-energy physicist who is also Director of the ATLAS Great Lakes Tier2 Center at the University of Michigan. “With perfSONAR, we can create a persistent baseline of performance in all segments of the network and see if any changes arise,” McKee said. “We can look at the ends of the network and if there is a problem, run on-demand tests using perfSONAR on the suspect segment.” (more)
Brian Tierney, ESnet -- “Once it’s up and running, perfSONAR can perform regular tests of a network,” said Tierney, a computer scientist based at the Lawrence Berkeley National Laboratory. “Basically every time we have worked with someone to set up perfSONAR and run some bandwidth tests, they have found what I call a ‘soft failure,’ where bandwidth on some path is 3 to 10 times slower then expected.”
Tierney has been developing tools to assess network performance for more than 10 years. These ongoing tests help differentiate temporary glitches from ongoing configuration problems. He notes that oftentimes soft failures are not obvious and can only be detected with close inspection.
“At first, I was kind of amazed at the number of soft failures we found using perfSONAR, but then I realized this is exactly what we were hoping to be able to do when we first started talking about perfSONAR 10 years ago,” Tierney said. “Of course, in a way this makes our jobs harder as perfSONAR finds more problems for us to fix.”
Below are links to use cases for various tools and services developed for perfSONAR-PS: