Synchronizing management information using traffic pattern matching technique
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Synchronizing Management Information using Traffic Pattern Matching Technique. Kohei Ohta, Yohsuke Takei, Nei Kato, Glenn Mansfield, Yoshiaki Nemoto C yber S olutions Inc., Tohoku University SPECTS’99, July 11-16, 1999. outline. background recent environment Internet measurement

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Synchronizing Management Information using Traffic Pattern Matching Technique

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Synchronizing Management Informationusing Traffic Pattern Matching Technique

Kohei Ohta, Yohsuke Takei, Nei Kato, Glenn Mansfield, Yoshiaki Nemoto

Cyber Solutions Inc., Tohoku University

SPECTS’99, July 11-16, 1999


  • background

    • recent environment

  • Internet measurement

    • black box in the measurement

  • approach with pattern match technique

    • traffic characteristics at a border of network

    • incoming/outgoing traffic characteristics

  • evaluation

    • sample application

  • conclusion


  • Internet traffic measurement

    • effective operation

    • management and analysis

      • planning networks

      • managing QoS, ….

  • Efforts

    • IETF-WG


    • Research

      • NIMI, INI, so many measurement research and tools




host A


measurement the Internet

server B


    • accounting

    • policing

    • shaping

  • who is speaking?

  • where is congested?

  • how far to the servers?


network A


server A

issues on high-speed network measurement

  • a large amount of traffic

    • difficult for exhaustive examination

  • rapid changing situation

    • the event handling is time sensitive

  • widely distributed

    • difficult to observe from one point



points of observation

  • points of observation

    • Interfaces of network devices

    • probing shared media

      • traditional Ethernet, FDDI/CDDI,…

    • remote monitoring

      • remote management, DISMAN, RMON

  • range of observation

    • inside LAN

    • large scale backbone network

    • end-to-end across global Internet

local area

wide area

synchronization issue

  • What is synchronization?

    • information correlation observed at different independent point

  • Why synchronize?

    • all network activities are related each other

    • to know the picture of global behavior

  • How to synchronize?

    • NTP, GPS

black box in the measurement

How to synchronize?

what is traffic pattern?

related activity?


modeling the traffic pattern

traffic transition vector

similarity evaluation

correlation coefficient (rij)

between incoming and outgoing traffic

experimental environment

  • two types of operational network

    • 100Mbps FDDI backbone network

      • providing connectivity to some big universities, colleges, and museums

      • over 20 organizations connected

    • 10Mbps Ethernet Internet-eXchange,

      • providing connectivity to 5 commercial ISPs.

data for evaluation

  • whole traffic data from the operational network

  • traffic data of each observation point derived from whole traffic

  • comparing the simulated data with original whole traffic data

overall evaluation

  • comparison between logged data and calculated data

the best case with exact match

(most strict evaluation)

sample synchronization result


what is the traffic in the network

LiI is amount of synchronizedincoming traffic via link i

who is using the bandwidth

traffic MATRIXin switching HUB

  • 100M Ethernet SW-HUB

  • 24-ports

  • Access method

    • SNMPv1

  • MIB object

    • ifInUcastPkts

    • ifOutUcastPkts

  • Polling Interval: 10sec.


  • Good points

    • suitable for high-speed network

    • small resources needed

    • within well-standardized framework, e.g. SNMP

    • no new additional equipment needed.

  • Limitations

    • only for small delay network

    • result is just estimation

    • difficult to apply to homogeneous network


  • On traffic measurement issues:

    • point out the strong requirement in case of high-speed network measurement in distributed manner.

    • proposed a novel idea to synchronize the traffic information observed at different independent points, which use traffic pattern match technique.

    • show the experimental result and sample application with this proposed technique.

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