Internet2 End-to-End Performance Initiative Eric L. Boyd Director of Performance Architecture and Technologies Internet2

Network support of Science Science is a global community Networks links scientists Collaborative research occurs across network boundaries For the scientist, the value of the network is the achieved network performance Scientists should not have to focus on the network; good end-to-end performance should be a given

Achieving Good End-to-End Performance Internet2 consists of: –Campuses –Regional networks –Internet2 backbone network Our members care about connecting with: –Other members –Government labs & networks –International partners The Internet2 community cares about making all of this work

Identifying the Problem Applications Developer System Administrator LAN Administrator Campus Networking Gigapop BackboneCampus Networking LAN Administrator System Administrator Applications Developer How do you solve a problem along a path? Hey, this is not working right! The computer Is working OK Talk to the other guysEverything is AOK No other complaints The network is lightly loaded All the lights are green We don’t see anything wrong Looks fine Others are getting in ok Not our problem

Status Quo Performance is excellent across backbone networks Performance is a problem end-to-end Problems are concentrated towards the edge and in network transitions We need to: –Diagnose: Understand limits of performance –Address: Work with members and application communities to address those performance issues

Vision: Performance Information is … Available –People can find it (Discovery) –“Community of trust” allows access across administrative domain boundaries (AA) Ubiquitous –Widely deployed (Paths of interest covered) –Reliable (Consistently configured correctly) Valuable –Actionable (Analysis suggests course of action) –Automatable (Applications act on data)

Getting There: Build & Empower the Community Decouple the Problem Space: Analysis and Visualization Performance Data Sharing Performance Data Generation Grow the Footprint: Clean APIs and protocols between each layer Widespread deployment of measurement infrastructure Widespread deployment of common performance measurement tools

Result: No more mystery … Increase network awareness –Set user expectations accurately Reduce diagnostic costs –Performance problems noticed early –Performance problems addressed efficiently –Network engineers can see & act outside their turf Transform application design –Incorporate network intuition into application behavior

From the scientist’s perspective Discover additional monitoring resources Authenticate locally Authorized to use remote network resources to a limited extent Acquire performance monitoring data from remote sites via standard protocol Innovate where needed –Customize the analysis and visualization

e-VLBI Network

eVLBI Result Use of integrated network monitoring helped to enable identification of bottleneck (hardware fault) Automated monitoring allowed view of network throughput variation over time –Highlights route changes, network outages Automated monitoring also helps to highlight any throughput issues at end points: –E.g. Network Interface Card failures, Untuned TCP Stacks Integrated monitoring provides overall view of network behavior at a glance

Internet2 End-to-End Performance Initiative (E2Epi) Includes: –Internet2 staff –Internet2 members –Federal partners –International partners Building: –Performance monitoring tools –Performance middleware frameworks –Performance improvement tools

Support for E2Epi Funded out of network revenues Partnerships –Leveraging GÉANT2, ESnet, and RNP resources through consortium leadership Grants –NSF SGER - Leveraging Internet2 Facilities for the Network Research Community –NSF SGER2 - Network Measurement for International Connections –NSF BTG - Bridging the Gap: End-to-End Networking for Landmark Applications –NLM Pilot - User Experience with the High Performance Internet Infrastructure: Critical Incidents of Success and Failure –NLM NDT - Enhancing the Web 100-based Network Diagnostic Tool

Performance Tools Diagnosis –Throughput (BWCTL) –One-Way Delay (OWAMP) –Top 10 Problems in First Mile (NDT) Solutions –Alternate congestion control (VFER) –Partition the session (Phoebus)

Network Performance Measurement Workshops –Example Course Materials: Goals: –Grow installed base of BWCTL/Iperf, OWAMP, and NDT at GigaPoP and regional campuses. –Begin integration into IT support processes. –Create an installed base for perfSONAR deployment. –Teach Internet2 community to use performance tools.

What is perfSONAR? Performance Middleware perfSONAR is an international consortium in which Internet2 is a founder and leading participant perfSONAR is a set of protocol standards for interoperability between measurement and monitoring systems perfSONAR is a set of open source web services that can be mixed-and-matched and extended to create a performance monitoring framework

perfSONAR Design Goals Standards-based Modular Decentralized Locally controlled Open Source Extensible Applicable to multiple generations of network monitoring systems Grows “beyond our control” Customized for individual science disciplines

perfSONAR Integrates Network measurement tools Network measurement archives Discovery Authentication and authorization Data manipulation Resource protection Topology

perfSONAR Credits perfSONAR is a joint effort: –ESnet –GÉANT2 JRA1 –Internet2 –RNP ESnet includes: –ESnet/LBL staff –Fermilab Internet2 includes: –University of Delaware –Georgia Tech –SLAC –Internet2 staff GÉANT2 JRA1 includes: –Arnes –Belnet –Carnet –Cesnet –CYNet –DANTE –DFN –FCCN –GRNet –GARR –ISTF –PSNC –Nordunet (Uninett) –Renater –RedIRIS –Surfnet –SWITCH

perfSONAR Adoption R&E Networks –Internet2 –ESnet –GÉANT2 –European NRENs –RNP Application Communities –LHC –GLORIAD Distributed Virtual NOC –Roll-out to other application communities in 2007 Distributed Development –Individual projects (10 before first release) write components that integrate into the overall framework –Individual communities (5 before first release) write their own analysis and visualization software

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