1 / 14

A TCP Tuning Daemon

A TCP Tuning Daemon. SC2002 November 19, 2002. Tom Dunigan thd@ornl.gov Matt Mathis mathis@psc.edu Brian Tierney bltierney@lbl.gov. Roadmap. www.net100.org. Motivation Net100 project Web100 network probes & sensors protocol analysis A TCP tuning daemon Tuning experiments.

thomasmjohnson
Download Presentation

A TCP Tuning Daemon

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A TCP Tuning Daemon SC2002 November 19, 2002 Tom Dunigan thd@ornl.gov Matt Mathis mathis@psc.edu Brian Tierney bltierney@lbl.gov

  2. Roadmap www.net100.org • Motivation • Net100 project • Web100 • network probes & sensors • protocol analysis • A TCP tuning daemon • Tuning experiments • … and now a word from our sponsors • DOE-funded project (Office of Science) • $1M/yr, 3 yrs beginning 9/01 • LBL, ORNL, PSC, NCAR • Net100 project objectives: (network-aware operating systems) • measure, understand, and improve end-to-end network/application performance • tune network protocols and applications (grid and bulk transfer) • first year emphasis: TCP bulk transfer over high delay/bandwidth nets

  3. Motivation • Poor network application performance • High bandwidth paths, but app’s slow • Is it application? OS? network? … Yes • Often need a network “wizard” • Changing: bandwidths • 9.6 Kbs… 1.5 Mbs ..45 …100…1000…? Gbs • Unchanging: TCP • speed of light (RTT) • MTU (still 1500 bytes) • TCP congestion avoidance • TCP is lossy by design ! • 2x overshoot at startup, sawtooth • recovery after a loss can be very slow on today’s high delay/bandwidth links • Recovery proportional to MSS/RTT2 8 Mbs Linear recovery at 0.5 Mb/s! Instantaneous bandwidth Early startup losses Average bandwidth ORNL to NERSC ftp GigE/OC12 80ms RTT

  4. TCP tuning • set optimal (?) buffer size • need buffer = bandwidth*RTTORNL/NERSC (80 ms, OC12) need 6 MB • avoid losses • modified slow-start • reduce bursts • anticipate loss (ECN,Vegas?) • reorder threshold • speed recovery • bigger MTU or “virtual MSS” • modified AIMD (0.5,1) • delayed ACKs and initial window • avoid congestion collapse • be fair (?) … intranets, QoS ns simulation: 500 mbs link, 80 ms RTT Packet loss early in slow start. Standard TCP with del ACK takes 10 minutes to recover!

  5. Net100 components for tuning • TCP protocol analysis • simulation/emulation • kernel tuning extensions • Web100 Linux kernel (NSF)www.web100.org • instrumented TCP stack (IETF MIB draft) • 100+ variables per flow (/proc/web100) • socket open/close event notification • API and tools for tracing and tuning, e.g., bw tester: http://firebird.ccs.ornl.gov:7123 • Path characterization • Network Tuning and Analysis Framework (NTAF) • both active and passive measurement • iperf, pipechar • schedule probes and distribute/archive results • data base of measurements • NTAF/Net100 hosts at PSC, NCAR,LBL,ORNL, NERSC,CERN,UT,SLAC • TCP tuning daemon

  6. TCP Tuning Daemon WAD config file [bob] src_addr: 0.0.0.0 src_port: 0 dst_addr: 10.5.128.74 dst_port: 0 mode: 1 sndbuf: 2000000 rcvbuf: 100000 wadai: 6 wadmd: 0.3 maxssth: 100 divide: 1 reorder: 9 sendstall: 0 delack: 0 floyd: 1 • Work-around Daemon (WAD) • tune unknowing sender/receiver at startup and/or during flow • Web100 kernel extensions • pre-set windowscale to allow dynamic tuning • uses netlink to alert daemon of socket open/close (or poll) • besides existing Web100 buffer tuning, new tuning options using WAD_* variables • knobs to disable Linux 2.4 caching, burst mgt., and sendstall • config file with static tuning data • mode specifies dynamic tuning (Floyd AIMD, NTAF buffer size, concurrent streams) • daemon periodically polls NTAF for fresh tuning data • written in C (also python version)

  7. Experimental results • Evaluating the tuning daemon in the wild • emphasis: bulk transfers over high delay/bandwidth nets (Internet2, ESnet) • tests over: 10GigE,OC48, OC12, OC3, ATM/VBR, GigE,FDDI,100/10T,cable, ISDN,wireless (802.11b),dialup • tests over NistNET 100T testbed • Various TCP tuning options • buffer tuning • AIMD mods (including Floyd, both in-kernel and in WAD) • slow-start mods • parallel vs single • Results are anecdotal • more systematic testing is on-going • Your mileage may vary …. Network professionals on a closed course. Do not attempt this at home.

  8. WAD tuning results • Classic buffer tuning • ORNL to PSC, OC12, 80ms RTT • network-challenged app. gets 10 Mbs • same app., WAD/NTAF tuned buffer gets 143 Mbs • Virtual MSS • tune TCP’s additive increase (WAD_AI) • add k segments per RTT during recovery • k=6 like GigE jumbo frame, but: • interrupt rate not reduced • doesn’t do k segments for initial window

  9. Tuning around Linux (2.4) TCP Amsterdam-Chicago GigE via 10GigE, 100 ms RTT • Tunable ssthresh caching • Tunable “sendstall” (TXQUELEN) 600 mbs Floyd AIMD: as cwnd grows increase AI and decrease MD, do the reverse when cwnd shrinks Added to Net100 kernel and to WAD (WAD tunable) Floyd AIMD sendstalls Standard AIMD UDP event

  10. WAD tuning • Modified slow-start and AI • ORNL to NERSC, OC12, 80 ms RTT • often losses in slow-start • WAD tuned Floyd slow-start and fixed AI (6) • WAD-tuned AIMD and slow-start • ORNL to CERN, OC12, 150ms RTT • parallel streams AIMD (1/(2k),k) • WAD-tuned single stream (0.125,4)

  11. GridFTP tuning Can tuned single stream compete with parallel streams? Mostly not with “equivalence” tuning, but sometimes…. Parallel streams have slow-start advantage. WAD can divide buffer among concurrent flows—fairer/faster? Tests inconclusive so far…. Testing on real Internet is problematic. Is there a “congestion metric”? Per unit of time? Flow Mbs congestion re-xmits untuned 28 4 30 tuned 74 5 295 parallel 52 30 401 untuned 25 7 25 tuned 67 2 420 parallel 88 17 440 Buffers: 64K I/O, 4MB TCP (untuned 64K TCP: 8 mbs, 200s) Data/plots from Web100 tracer

  12. Future TCP tuning • Reorder threshold • seeing more out of order packets • WAD tune a bigger reorder threshold for path • 40x improvement! • Linux 2.4 does a good job already • adjusts and caches reorder threshold • “undo” congestion avoidance LBL to ORNL (using our TCP-over-UDP) : dup3 case had 289 retransmits, but all were unneeded! • Delayed ACKs • WAD could turn off delayed ACKs -- 2x improvement in recovery rate and slow-start • Linux 2.4 already turns off delayed ACKs for initial slow-start ns simulation: 500 mbs link, 80 ms RTT Packet loss early in slow-start. Standard TCP with del ACK takes 10 minutes to recover! NOTE aggressive static AIMD (Floyd pre-tune)

  13. Futures • Net100 • analyze effectiveness/fairness of current tuning options • simulation • emulation • on the net (systematic tests) • NTAF probes -- characterizing a path to tune a flow • router data (passive) • monitoring applications with Web100 • additional tuning algorithms • Vegas,ECN • non-TCP • identify non-congestive loss? • parallel/multipath selection/tuning • WAD-to-WAD tuning • jumbo frames experiments… the quest for bigger and bigger MTUs • more user-friendly • Web100 extensions • refine user interface and API • port to other OS’s

  14. Summary www.net100.org • Novel approaches • non-invasive dynamic tuning of legacy applications • using TCP to tune TCP (Web100) • tuning on a per flow/destination • Effective evaluation framework • protocol analysis and tuning + net/app/OS debugging • out-of-kernel tuning • Beneficial interactions • TCP protocols (Floyd, Wu Feng (DRS), Web100, parallel/non-TCP) • Path characterization research (SciDAC, CAIDA, Pinger) • Scientific application and Data grids (SciDAC, CERN) • Performance improvements

More Related