Behavior Dynamics in Media-Sharing Social Networks

351 Pages·2011·3.272 MB·English

by  H. Vicky Zhao, W. Sabrina Lin, K. J. Ray Liu

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BehaviorDynamicsinMedia-SharingSocialNetworks
Inlarge-scalemedia-sharingsocialnetworks,wheremillionsofuserscreate,share,link,
and reuse media content, there are clear challenges in protecting content security and
intellectualproperty,andindesigningscalableandreliablenetworkscapableofhandling
highlevelsoftraffic.
Thiscomprehensiveresourcedemonstrateshowgametheorycanbeusedtomodeluser
dynamics and optimize design of media-sharing networks. It reviews the fundamental
methodologiesusedtomodelandanalyzehumanbehavior,usingexamplesfromreal-
worldmultimediasocialnetworks.Withathoroughinvestigationoftheimpactofhuman
factorsonmultimediasystemdesign,thisaccessiblebookshowshowanunderstanding
ofhumanbehaviorcanbeusedtoimprovesystemperformance.
Bringingtogethermathematicaltoolsandengineeringconceptswithideasfromsoci-
ology and human behavior analysis, this one-stop guide will enable researchers to
explore this emerging field further and ultimately design media-sharing systems with
moreefficient,secure,andpersonalizedservices.
H.VickyZhao is an Assistant Professor in the Department of Electrical and Computer
EngineeringattheUniversityofAlberta.TherecipientoftheIEEESignalProcessing
Society Young Author Best Paper Award 2008, she is an Associate Editor for the
IEEE Signal Processing Letters and the Journal of Visual Communication and Image
Representation.
W. Sabrina Lin is a Research Associate in the Department of Electrical and Computer
Engineering at the University of Maryland. She received the University of Maryland
FutureFacultyFellowshipin2007.
K.J.RayLiuisaDistinguishedScholar-TeacheroftheUniversityofMaryland,wherehe
isChristineKimEminentProfessorinInformationTechnology.HereceivedtheIEEE
Signal Processing Society Technical Achievement Award in 2009, and was Editor-in-
ChiefoftheIEEESignalProcessingMagazineandthefoundingEditor-in-Chiefofthe
EURASIPJournalonAdvancesinSignalProcessing.

Behavior Dynamics in
Media-Sharing Social Networks
H. VICKY ZHAO
UniversityofAlberta,Canada
W. SABRINA LIN
UniversityofMaryland,CollegePark
K. J. RAY LIU
UniversityofMaryland,CollegePark
CAMBRIDGEUNIVERSITYPRESS
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CambridgeUniversityPress
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PublishedintheUnitedStatesofAmericabyCambridgeUniversityPress,NewYork
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Informationonthistitle:www.cambridge.org/9780521197274
(cid:2)C CambridgeUniversityPress2011
Thispublicationisincopyright.Subjecttostatutoryexception
andtotheprovisionsofrelevantcollectivelicensingagreements,
noreproductionofanypartmaytakeplacewithoutthewritten
permissionofCambridgeUniversityPress.
Firstpublished2011
PrintedintheUnitedKingdomattheUniversityPress,Cambridge
AcataloguerecordforthispublicationisavailablefromtheBritishLibrary
LibraryofCongressCataloguinginPublicationdata
Zhao,H.Vicky,1976–
Behaviordynamicsinmedia-sharingsocialnetworks/H.VickyZhao,W.SabrinaLin,K.J.RayLiu.
p. cm.
Includesbibliographicalreferencesandindex.
ISBN978-0-521-19727-4(hardback)
1.Socialnetworks. 2.Consumerbehavior. 3.Humanbehavior. 4.Gametheory. I.Lin,W.Sabrina,
1981– II.Liu,K.J.Ray,1961– III.Title.
HM742.Z46 2011
302.30285(cid:3)675–dc22 2011006139
ISBN 978-0-521-19727-4Hardback
CambridgeUniversityPresshasnoresponsibilityforthepersistenceor
accuracyofURLsforexternalorthird-partyinternetwebsitesreferredto
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ToOurFamilies

Contents
Preface pagexi
PartI Introduction 1
1 Introductiontomedia-sharingsocialnetworks 3
1.1 Quantitativeanalysisofsocialnetworks 5
1.2 Understandingmediasemanticsinmedia-sharingnetworks 10
2 Overviewofmultimediafingerprinting 14
2.1 Traitor-tracingmultimediafingerprinting 15
2.2 Scalablevideocodingsystem 17
2.3 Scalablevideofingerprinting 18
3 Overviewofmesh-pullpeer-to-peervideostreaming 24
3.1 Mesh-pullstructureforP2Pvideostreaming 25
3.2 Userdynamicsinpeer-to-peervideostreaming 33
4 Gametheoryforsocialnetworks 41
4.1 Noncooperativeandcooperativegames 42
4.2 Noncooperativegames 43
4.3 Bargaininggames 50
PartII Behaviorforensicsinmedia-sharingsocialnetworks 55
5 Equal-riskfairnessincolludersocialnetworks 57
5.1 Equal-riskcollusion 57
5.2 Influenceonthedetector’sside:collusionresistance 63
5.3 Traitor-tracingcapabilityofscalablefingerprints 75
5.4 Chaptersummaryandbibliographicalnotes 82
viii Contents
6 Leveragingsideinformationincolludersocialnetworks 85
6.1 Probingandusingsideinformation 85
6.2 Game-theoreticanalysisofcolluderdetectordynamics 93
6.3 Equilibriumanalysis 94
6.4 Simulationresults 103
6.5 Chaptersummaryandbibliographicalnotes 109
7 Risk–distortionanalysisofmultiusercollusion 111
7.1 Videofingerprinting 112
7.2 Risk–distortionmodeling 113
7.3 Strategieswithsideinformation 117
7.4 Parameterestimation 122
7.5 Simulationresults 122
7.6 Chaptersummaryandbibliographicalnotes 127
PartIII Fairnessandcooperationstimulation 129
8 Game-theoreticmodelingofcolludersocialnetworks 131
8.1 Multiusercollusiongame 132
8.2 FeasibleandParetooptimalcollusion 137
8.3 Whentocollude 139
8.4 Howtocollude:thebargainingmodel 150
8.5 Howtocollude:examples 155
8.6 Maximumpayoffcollusion 160
8.7 Chaptersummaryandbibliographicalnotes 167
9 Cooperationstimulationinpeer-to-peervideostreaming 169
9.1 IncentivesforpeercooperationovertheInternet 170
9.2 Wirelesspeer-to-peervideostreaming 178
9.3 Optimalcooperationstrategiesforwirelessvideostreaming 181
9.4 OptimalchunkrequestalgorithmforP2Pvideostreamingwith
scalablecoding 189
9.5 Chaptersummaryandbibliographicalnotes 193
10 Optimalpricingformobilevideostreaming 195
10.1 Introduction 195
10.2 Systemmodel 196
10.3 Optimalstrategiesforsinglesecondarybuyer 198
10.4 Multiplesecondarybuyers 206
10.5 Optimalpricingforthecontentowner 208
10.6 Chaptersummaryandbibliographicalnotes 217