my experiences results and remarks to tcp bw and ct measurements tools
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My Experiences, results and remarks to TCP BW and CT Measurements Tools. Jiří Navrátil SLAC. My interests concerns o n. How to achieve full BW utilization Analysis of Tools for BW estimation New methods of CT detection. Inspira tion Les Cottrell IEPM metrics

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my experiences results and remarks to tcp bw and ct measurements tools

My Experiences, results and remarks to TCP BW and CT Measurements Tools

Jiří Navrátil

SLAC

slide2

My interests concerns on

  • How to achieve full BW utilization
  • Analysis ofTools for BW estimation
  • New methods of CT detection
slide3

Inspiration

    • Les Cottrell IEPM metrics
    • Jin Gujun (LBNL) netest-2 recommendation
    • Feng Wu-Chun (LANL) simulations
    • Diana Katabi, Charles Blake (MIT) bottleneck detection
slide4

Area of saturation = area of full utilization

    • TCP windows size (not sufficient for HSL)
    • Parallel streams
    • combination
slide12

Internet path

Out

In

Virtual queue

problems of slow and high loaded lines
Problems of slow and high loaded lines
  • All parallel streams share same “virtual queue”
  • All “my traffic” share same queue with outside CTvisible in statistics for “streams speed”visible in time reports (In iperf)
slide21

Conclusion:

The other TCP applications behave very similarly in same environment

But not all applications are so aggressive as Iperf !

used tools for bw estimations
Used tools for BW estimations
  • Pathrate
  • Pathload
  • Iperf
  • Netest-2
  • Incite BWe
  • UDPmon
short characteristic of methods
Short characteristic of methods

Patharate

+ accurate

- not very reliable, long run time

Pathload

+ accurate, fast, light

- limited range of operation ( < 155 Mbps)

short characteristic of methods1
Short characteristic of methods

Iperf

+ reliable

- must be configured to use full BW and postprocessed

- heavy load of lines during operation

Netest-2

+ reliable, good reports

- must be configured to use full BW,

- accurate (different timing scheme)

slide32

INCITE: Edge-based Traffic Processing and Service Inference for High-Performance Networks

Richard Baraniuk, Rice University; Les Cottrell, SLAC; Wu-chun Feng, LANL

Incite

BW estimator

slide33

P2

P1

BWe ~f(VQ) =f(dTR) dTR <0,RTT>

dTS

(20 ms)

Time

P1

P2

P1

P2

dtp2

dTR

RTT

P1

P2

dtp1

slide37

freq= volume/dt

volume ~ pkt_length*8

dt ~ F(VQ) ~ F(Internet)

BWe=Mean(freq)

Open Problem

What is pkt_length?

slide38

All “my test traffic” share same queue with outside CT

  • (It means that delay caused to my pkts by VQ
  • is not dependent only on my pkt_lengths !)
  • The accuracy is dependent on knowlegde of
  • packet distribution on particular path.
  • The average packet length ~1000 bytes
  • gives reasonable results.

Virtual queue

slide51

Filtering & Averaging

ANL

Current/Average

CERN

Current/Average

slide55

KPNQest

UK-problems

slide57

INCITE: Edge-based Traffic Processing and Service Inference for High-Performance Networks

Richard Baraniuk, Rice University; Les Cottrell, SLAC; Wu-chun Feng, LANL

Incite

CT detection

CT = f (dTR)

mf ct features and benefits
MF-CT Features and benefits
  • No need access to routers !
    • Current monitoring systems for Load of traffic are based on SNMP or Flows (needs access to routers)
  • Low cost:
    • Allows permanent monitoring (20 pkts/sec ~ overhead 10 Kbytes/sec)
    • Can be used as data provider for ABW prediction (ABW=BW-CT)
  • We have 2 data points of CT per second !!
  • Weak point for common use

MATLAB code

slide69

MF-CT verification model

UDP echo

SNMP counter

CERN

SNMP counter

internet

SNMP counter

IN2P3

SLAC

SNMP counter

MF-CT Simulator

UDP echo

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