Peer Assisted CDN

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    Peer-Assisted ContentPeer-Assisted Content

    Distribution Networks:Distribution Networks: Techniques and Challenges Techniques and Challenges Pei CaoPei Cao

    Stanford UniversitStanford Universit

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     Traditional !ntra-Provider Traditional !ntra-Provider

    Content Distribution Networks Content Distribution Networks

    National Center 

    Regional Center 

    Branch

    . . .

    . . . . . .

    Users . . . . . .. . . . . .

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    Peer-to-Peer ContentPeer-to-Peer Content

    Distribution Distribution

    National Center 

    Regional Center 

    Branch

    . . .

    . . . . . .

    Users . . . . . .. . . . . .

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    P"P vs CDNP"P vs CDN

    # P"P:P"P: $ No infrastructure costNo infrastructure cost

    $ Su%%l grows linearl with de&andSu%%l grows linearl with de&and

    $ Si&%le distributed' rando&i(ed algorith&sSi&%le distributed' rando&i(ed algorith&s

    $ No )oSNo )oS

    # CDN:CDN:

    $ !nitial infrastructure cost!nitial infrastructure cost $ Centrali(ed scheduling algorith&sCentrali(ed scheduling algorith&s

    $ Network e*ciencNetwork e*cienc

    $ Ca%able of su%%orting )oSCa%able of su%%orting )oS

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    Co&bine P"P with CDN+Co&bine P"P with CDN+

    # Use P"P to co&%le&ent CDNUse P"P to co&%le&ent CDN $ P"P reduces load on the CDN' covers areasP"P reduces load on the CDN' covers areas

    where CDN is not installedwhere CDN is not installed

    $ ,ust be able to control' or sha%e.' P"P tra*c,ust be able to control' or sha%e.' P"P tra*c # Use CDN to co&%le&ent P"PUse CDN to co&%le&ent P"P

    $ CDN ste%s in when %eer-based distribution isCDN ste%s in when %eer-based distribution is

    falling short' enabling )oSfalling short' enabling )oS

    $ ,ust be able to detect when %eers won/t &eet,ust be able to detect when %eers won/t &eet the deliver ti&e guaranteethe deliver ti&e guarantee

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    0utline0utline

    # 1eview of 2itTorrent1eview of 2itTorrent

    # Tra*c-sha%ing 2itTorrent: biased Tra*c-sha%ing 2itTorrent: biased neighbor selectionneighbor selection

    # )oS in 2itTorrent: deliver ti&e)oS in 2itTorrent: deliver ti&e %rediction%rediction

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    2itTorrent 3ile Sharing2itTorrent 3ile Sharing

    NetworkNetwork 4oal: re%licate 5 chunks of data a&ong4oal: re%licate 5 chunks of data a&ong

    N nodesN nodes

    # 3or& neighbor connection gra%h3or& neighbor connection gra%h

    # Neighbors e6change dataNeighbors e6change data

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    2itTorrent: Neighbor2itTorrent: Neighbor

    SelectionSelection  Tracker 7le8torrent9Seed

    hole 7le

    A

    ;

    " <

    =

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    2itTorrent: Piece 1e%lication2itTorrent: Piece 1e%lication

     Tracker 7le8torrent9Seed

    hole 7le

    A

    ;

    <

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    2itTorrent: Piece 1e%lication2itTorrent: Piece 1e%lication

    Algorith&s Algorith&s

    #  Tit-for-tat. >choking?unchoking@: Tit-for-tat. >choking?unchoking@: $ ach %eer onl u%loads to B other %eers at a ti&each %eer onl u%loads to B other %eers at a ti&e

    $  of these are chosen based on a&ount of data of these are chosen based on a&ount of data

    received fro& the neighbor in the last " secondsreceived fro& the neighbor in the last " seconds

    $  The last one is chosen rando&l' with a B;E bias The last one is chosen rando&l' with a B;E bias

    toward newco&erstoward newco&ers

    # >Focal@ 1arest-7rst re%lication:>Focal@ 1arest-7rst re%lication: $ hen %eer < unchokes %eer A' A selects whichhen %eer < unchokes %eer A' A selects which

    %iece to download%iece to download

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    Analsis of 2itTorrentAnalsis of 2itTorrent

    # Conclusion fro& &odeling studies:Conclusion fro& &odeling studies: 2itTorrent is nearl o%ti&al in2itTorrent is nearl o%ti&al in

    ideali(ed' ho&ogeneous networksideali(ed' ho&ogeneous networks $ De&onstrated b si&ulation studiesDe&onstrated b si&ulation studies

    $ Con7r&ed b theoretical &odeling studiesCon7r&ed b theoretical &odeling studies

    # !ntuition: in a rando& gra%h'!ntuition: in a rando& gra%h'

    Prob>Peer A/s content is a subset of Peer 2/s@ GProb>Peer A/s content is a subset of Peer 2/s@ G

    ;E;E

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     Tra*c-Sha%ing 2itTorrent Tra*c-Sha%ing 2itTorrent

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    1ando& Neighbor 4ra%h1ando& Neighbor 4ra%h

    # 6isting studies all assu&e rando&6isting studies all assu&e rando& neighbor selectionneighbor selection

    $ 2itTorrent no longer o%ti&al if nodes in2itTorrent no longer o%ti&al if nodes in the sa&e !SP onl connect to each otherthe sa&e !SP onl connect to each other

    # 1ando& neighbor selection1ando& neighbor selection  highhigh

    cross-!SP tra*ccross-!SP tra*c

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    Di*cult in Tra*c-Sha%ing P"PDi*cult in Tra*c-Sha%ing P"P

    A%%licationsA%%lications

    # !SPs:!SPs: $ DiHerent links have diHerent &onetar costsDiHerent links have diHerent &onetar costs

    $ Prefer clustering. of tra*cPrefer clustering. of tra*c # P"P A%%lications:P"P A%%lications:

    $ No knowledge of underling !SP to%ologNo knowledge of underling !SP to%olog

    $ Use rando&i(ed algorith&s that don/t doUse rando&i(ed algorith&s that don/t dowell under clusteringwell under clustering

    # Current solution: throttlingCurrent solution: throttling  usersusers suHersuHer

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    A Network-3riendlA Network-3riendl

    2itTorrent+2itTorrent+ # !SPs infor& 2itTorrent of its link!SPs infor& 2itTorrent of its link

    %references%references

    # Algorith& of 2itTorrent is adIustedAlgorith& of 2itTorrent is adIusted such that both users and !SPs bene7tsuch that both users and !SPs bene7t

    # 6a&%le: 2iased Neighbor Selection6a&%le: 2iased Neighbor Selection $ orks when cost function is transitiveorks when cost function is transitive

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    2iased Neighbor Selection2iased Neighbor Selection

    # !dea: of N neighbors' choose N-k fro&!dea: of N neighbors' choose N-k fro& %eers in the sa&e !SP' and choose k%eers in the sa&e !SP' and choose k

    rando&l fro& %eers outside the !SP rando&l fro& %eers outside the !SP

    !SP

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    !&%le&enting 2iased Neighbor!&%le&enting 2iased Neighbor

    SelectionSelection

    # 2 Tracker2 Tracker $ Need !SP a*liations of %eersNeed !SP a*liations of %eers

    #Peer to AS &a%sPeer to AS &a%s#Public !P address ranges fro& !SPsPublic !P address ranges fro& !SPs #S%ecial J-. KTTP headerS%ecial J-. KTTP header

    # 2 tra*c sha%ing devices2 tra*c sha%ing devices $ !nterce%t %eer!nterce%t %eer  tracker. &essagestracker. &essages

    and &ani%ulate res%onsesand &ani%ulate res%onses

    $ No need to change tracker or clientNo need to change tracker or client

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    valuation ,ethodologvaluation ,ethodolog

    # vent-driven si&ulatorvent-driven si&ulator $ Use actual client and tracker codes as &uch asUse actual client and tracker codes as &uch as

    %ossible%ossible

    $ Calculate bandwidth contention' assu&e %erfect fair-Calculate bandwidth contention' assu&e %erfect fair-

    share fro& TCPshare fro& TCP

    # Network settingsNetwork settings $ 9= !SPs' each with ; %eers' 95b?s u%load' 9,b?s9= !SPs' each with ; %eers' 95b?s u%load' 9,b?s

    downloaddownload

    $ Seed node' =5b?s u%loadSeed node' =5b?s u%load

    $ 0%tional universit. nodes >9,b?s u%load@0%tional universit. nodes >9,b?s u%load@

    $ 0%tional !SP bottleneck to other !SPs0%tional !SP bottleneck to other !SPs

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    Fi&itation of ThrottlingFi&itation of Throttling

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