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ISP-Friendly Peer Matching. Cheng-Hsin Hsu, Nitin Chiluka, and Mohamed Hefeeda School of Computing Science, Simon Fraser University, Canada. 1. Motivation. 2. Big Picture. P2P costs ISPs more money Challenge: find senders to reduce loads on inter-ISP links improve application performance

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ISP-Friendly Peer Matching

Cheng-Hsin Hsu, Nitin Chiluka, and Mohamed Hefeeda

School of Computing Science, Simon Fraser University, Canada

1. Motivation

2. Big Picture

  • P2P costs ISPs more money

  • Challenge: find senders to

    • reduce loads on inter-ISP links

    • improve application performance

  • Solution: ISP-friendly matching

    • find senders to minimize AS distance

    • within AS, get closer senders by IP prefix

  • Match senders online using oracle

    • faster distance lookup

    • smaller data structure in memory

    • exact/approximate distance

  • Infer AS distance offline distance oracle

    • leverage public info

    • efficient inference algorithm

3. Our Approach

  • V : all ASes; L : stub ASes  Most ASes are in L (87%)

  • Construct_Distance_Oracle

  • For , compute shortest up-hill distance

  • For , compute valley-free distance

  • For and , compute valley-free distance

  • For , compute valley-free distance

  • Compute shortest valley-free AS paths

    • valley-free: customer AS does not transit data for its providers

  • Current algorithms [e.g., Mao 05]

     time

    • runs in ~ 2 days (25,000+ ASes)

    • needs ~ 625 MB memory

  • Our proposed algorithm

    • preprocess AS graph  concise data structure: Core Matrix

    • exclude stub ASes; they don’t transit traffic for any other ASes

    • runs in ~ 3 hours

    • needs ~ 10 MB memory (1.7 %)

Step 1

Step 2

Step 3

Determine distance for stub t is

a couple of comparisons

Only Core matrix is stored

 Small memory footprint

5. Work-in-Progress

4. Sample Results

  • Improve accuracy of AS distance inference (~70 %)

  • Even more compact data structure

    • recursively remove stub ASes

  • Real implementations and measurements

    • BitTorrent, peer-assisted CDN

  • http://nsl.cs.sfu.ca/wiki

  • For AS relationship

    info from CAIDA on

    2008/06/23

  • Client IPs:

    • 147, 822 from BitTorrent trackers

    • 160, 543 from CBC/Radio-Canada servers

CBC, 2000 Potential Senders

BitTorrent, 10 Senders

Up to 15times reduction on Inter-ISP traffic


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