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INCITE – Edge-based Traffic Processing for High-Performance Networks R. Baraniuk, E. Knightly, R. Nowak, R. Riedi Rice University L. Cottrell, J. Navratil,

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Presentation on theme: "INCITE – Edge-based Traffic Processing for High-Performance Networks R. Baraniuk, E. Knightly, R. Nowak, R. Riedi Rice University L. Cottrell, J. Navratil,"— Presentation transcript:

1 INCITE – Edge-based Traffic Processing for High-Performance Networks R. Baraniuk, E. Knightly, R. Nowak, R. Riedi Rice University L. Cottrell, J. Navratil, W. Mathews SLAC W. Feng, M. Gardner LANL web site: incite.rice.edu

2 incite.rice.eduINCITE Project – Rice, SLAC, LANL 2 INCITE Project InterNet Control and Inference from The Edge on-line tools to characterize and map host and network performance as a function of time, space, application, protocol, and service

3 incite.rice.eduINCITE Project – Rice, SLAC, LANL 3 INCITE Thrusts and Tools Thrust 1:Multiscale traffic analysis and modeling techniques owavelet, multifractal, connection-level models Thrust 2:Inference and control algorithms for network paths, links, and routers oend-to-end path probing and modeling onetwork tomography and topology discovery oadvanced high-speed protocols Thrust 3:Data collection tools oactive measurement infrastructure opassive application-layer measurement

4 incite.rice.eduINCITE Project – Rice, SLAC, LANL 4 pathChirp Goal –estimate instantaneous available bandwidth (ABW) on an end-to-end network link Basic probing paradigm –stream packets at some rate  no queuing delay  rate<ABW  queuing delay builds up  rate>ABW Until now: tradeoff –high accuracy has required high volume probing (inefficient) Unique to pathChirp –variable rate probe packet train (exponentially spaced chirp) –10x more efficient than competing techniques

5 incite.rice.eduINCITE Project – Rice, SLAC, LANL 5 Network Tomography From end-to-end measurements… … infer internal topology and delay/loss characteristics

6 incite.rice.eduINCITE Project – Rice, SLAC, LANL 6 TCP - Low Priority TCP alone 745.5 Kb/s TCP plus 739.5 Kb/s TCP-LP 109.5 Kb/s TCP-LP is invisible to TCP Goal –utilize excess bandwidth in a non-intrusive fashion Methodology –sender-side modification of TCP: delay-based approach Applications –bulk data transfers –available bandwidth monitoring –P2P file sharing High-speed TCP-LP –TCP-LP + HSTCP –implementation  Linux-2.4.22-web100 –experiments  Stanford - Ann Arbor  Stanford - Gainesville

7 incite.rice.eduINCITE Project – Rice, SLAC, LANL 7 Advanced TCP stacks Standard TCP (Reno) has problems on today’s long- distance high-speed networks (e.g. trans ocean/continent > hundreds of Mbits/s) Advanced TCP stacks (e.g. FAST, High-speed, TCP-LP …) and new rate based UDP transports address this issue We have evaluated many (~10) new implementations for throughput, stability, fairness, ease of use etc. BaBar (HENP) tier A sites (e.g. SLAC, IN2P3 (Lyon Fr) and FZK (Karlsruhe)) now starting to use chosen TCP stack for production transfer of Monte Carlo data to SLAC –Easier to use than multi-stream TCP, only optimize one parameter (window size)

8 incite.rice.eduINCITE Project – Rice, SLAC, LANL 8 Changes in network topology (BGP) can result in dramatic changes in performance Snapshot of traceroute summary table Samples of traceroute trees generated from the table ABwE measurement one/minute for 24 hours Thu 9 Oct 9:00am to Fri 10 Oct 9:01am Drop in performance (From original path: SLAC-CENIC-Caltech to SLAC-Esnet-LosNettos (100Mbps) -Caltech ) Back to original path Changes detected by IEPM-Iperf and AbWE Esnet-LosNettos segment in the path (100 Mbits/s) Hour Remote host Dynamic BW capacity (DBC) Cross-traffic (XT) Available BW = (DBC-XT) Mbits/s Note: 1. Caltech misrouted via Los-Nettos 100Mbps commercial net 14:00-17:00 2. ESnet/GEANT working on routes from 2:00 to 14:00 Los-Nettos (100Mbps)

9 incite.rice.eduINCITE Project – Rice, SLAC, LANL 9 Crossing the Application/Network Divide Application TCP IP Data Link Network Send data over network Segmentation Fragmentation Flow & Congestion Control Checksums :::: Implications to the application? Insights for high- performance network protocols? Network monitors focus here.

10 incite.rice.eduINCITE Project – Rice, SLAC, LANL 10 TICKET and MAGNET+MUSE TICKET: Traffic Information-Collecting Kernel with Exact Timing MAGNeT: Monitor for Application-Generated Network Traffic MUSE: MAGNET User-Space Environment Application TCP IP Data Link Network MAGNETMAGNET Send data over network Segmentation Fragmentation Flow & Congestion Control Checksums MUSE TICKET: tcpdump++ :::: For more information, go to www.lanl.gov/radiant/pubs.html

11 incite.rice.eduINCITE Project – Rice, SLAC, LANL 11 MAGNeT  MAGNET Monitoring Apparatus for General kerNel-Event Tracing (at nanoscale granularity) Why not extend monitoring to kernel events in general? Software Oscilloscope for Cluster and Grids –Debugging  e.g., IdentifiedLinux OS bug in the scheduler for SMPs.  Can be used to deploy, debug, and monitor the DOE UltraNet (UltraScienceNet), e.g., dynamic provisioning. –Performance Optimization  Improved performance of 10GigE adapters by 300%. Can improve end-to-end performance of DOE UltraNet. –Monitoring Grid Applications  Integrated MAGNET with SciDAC’s PERC TAU and SciDAC’s PERC SvPablo/Autopilot.* –Adaptive Resource-Aware Applications SciDAC Deployment: PERC, Supernova Science Ctr, Transit Network Fabric + Terascale Supernova Initiative + Fusion Energy (emerging), and Earth Systems Grid II (emerging). * For more information, see M. Gardner, W. Deng, T. Markham, C. Mendes, W. Feng, and D. Reed, “A High-Fidelity Software Oscilloscope for Globus,” GlobusWorld 2004, Jan. 2004.


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