Table Of ContentOpportunistic
Mobile Social
Networks
TThhiiss ppaaggee iinntteennttiioonnaallllyy lleefftt bbllaannkk
Opportunistic
Mobile Social
Networks
Edited by
Jie Wu and Yunsheng Wang
CRC Press
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Version Date: 20140603
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Dedication
Toourparents,ZengchangWu,YeyiShao,KemingWang,andYingyanWang
TThhiiss ppaaggee iinntteennttiioonnaallllyy lleefftt bbllaannkk
Contents
Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
ListofFigures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix
ListofTables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxvii
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxix
AbouttheEditors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xxxiii
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxxv
1 Social-CommunicationCompositeNetworks . . . . . . . . . . . . . . 1
PrithwishBasu,BenBaumer,AmotzBar-Noy,andChi-KinChau
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1.1 RelatedWork . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 CompositeGraphModels . . . . . . . . . . . . . . . . . . . . . . 5
1.2.1 MetricsonCompositeGraphs . . . . . . . . . . . . . . . . 5
1.3 CompositeStretchAnalysis . . . . . . . . . . . . . . . . . . . . . 8
1.3.1 TheoreticalResults . . . . . . . . . . . . . . . . . . . . . . 8
1.3.2 CompositeStretchofSomeSpecialGraphs . . . . . . . . . 10
1.3.3 Averagevs.Worst-CaseAnalysis . . . . . . . . . . . . . . 13
1.4 CompositeBroadcastTime . . . . . . . . . . . . . . . . . . . . . . 14
1.5 CompositeBetweennessCentrality . . . . . . . . . . . . . . . . . 17
1.5.1 ConstrainedCompositeLoadonPathGraphs . . . . . . . . 17
1.5.2 CompositeCentralityinManhattanGridNetworks . . . . . 17
1.6 MulticastinCompositeNetworks . . . . . . . . . . . . . . . . . . 18
1.6.1 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.6.2 Hierarchy-CompliantMulticast . . . . . . . . . . . . . . . 20
1.6.3 AlgorithmsforH-CompliantMulticast . . . . . . . . . . . 21
vii
viii (cid:4) Contents
1.7 Simulation-BasedEvaluation . . . . . . . . . . . . . . . . . . . . 24
1.7.1 ChainofCommand . . . . . . . . . . . . . . . . . . . . . . 24
1.7.1.1 EvaluationofBasicCompositeNetworkMetrics . 28
1.7.1.2 EvaluationofCompositeNetworkMulticast . . . 30
1.7.2 Friend-of-a-Friend(FOAF) . . . . . . . . . . . . . . . . . . 31
1.8 ConclusionandDiscussion . . . . . . . . . . . . . . . . . . . . . . 33
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2 RecentAdvancesinInformationDiffusionandInfluenceMaximization
ofComplexSocialNetworks . . . . . . . . . . . . . . . . . . . . . . . 37
HuiyuanZhang,SubhankarMishra,andMyT.Thai
2.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
2.3 SocialInfluenceandInfluenceMaximization . . . . . . . . . . . . 40
2.4 InformationDiffusionModels . . . . . . . . . . . . . . . . . . . . 42
2.4.1 ThresholdModels . . . . . . . . . . . . . . . . . . . . . . 43
2.4.1.1 LinearThresholdModel . . . . . . . . . . . . . . 44
2.4.1.2 TheMajorityThresholdModel . . . . . . . . . . 45
2.4.1.3 TheSmallThresholdModel . . . . . . . . . . . . 45
2.4.1.4 TheUnanimousThresholdModel . . . . . . . . . 45
2.4.1.5 OtherExtensions . . . . . . . . . . . . . . . . . 46
2.4.2 CascadingModel . . . . . . . . . . . . . . . . . . . . . . . 46
2.4.2.1 IndependentCascadingModel . . . . . . . . . . 46
2.4.2.2 DecreasingCascadingModel . . . . . . . . . . . 47
2.4.2.3 Independent Cascading Model with Negative
Opinion . . . . . . . . . . . . . . . . . . . . . . 47
2.4.3 GeneralizedThresholdandCascadeModels . . . . . . . . . 47
2.4.4 EpidemicModel . . . . . . . . . . . . . . . . . . . . . . . 48
2.4.4.1 SIRModel . . . . . . . . . . . . . . . . . . . . . 49
2.4.4.2 SISModel . . . . . . . . . . . . . . . . . . . . . 50
2.4.4.3 SIRSModel . . . . . . . . . . . . . . . . . . . . 50
2.4.5 CompetitiveInfluenceDiffusionModels . . . . . . . . . . . 50
2.4.5.1 Distance-BasedModel. . . . . . . . . . . . . . . 51
2.4.5.2 WavePropagationModel . . . . . . . . . . . . . 51
2.4.5.3 Weight-ProportionalThresholdModel . . . . . . 52
2.4.5.4 SeparatedThresholdModel . . . . . . . . . . . . 53
2.5 InfluenceMaximizationandApproximationAlgorithms . . . . . . 53
2.5.1 InfluenceMaximization . . . . . . . . . . . . . . . . . . . 53
2.5.2 ApproximationAlgorithm . . . . . . . . . . . . . . . . . . 55
2.5.2.1 GreedyAlgorithm . . . . . . . . . . . . . . . . . 55
2.5.2.2 CELFSelectionAlgorithm . . . . . . . . . . . . 56
2.5.2.3 CELF++Algorithm . . . . . . . . . . . . . . . . 57
2.5.2.4 SPMandSP1M . . . . . . . . . . . . . . . . . . 59
2.5.2.5 MaximumInfluencePaths . . . . . . . . . . . . . 59
2.5.2.6 SIMPATH . . . . . . . . . . . . . . . . . . . . . 61
Contents (cid:4) ix
2.5.2.7 VirAds . . . . . . . . . . . . . . . . . . . . . . . 63
2.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3 CharacterizingLinkConnectivityinOpportunisticNetworks . . . . . 71
Chul-HoLeeandDoYoungEun
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.2 Mobility-InducedLink-LevelMetricsandNetworkPerformance . . 73
3.2.1 MathematicalDefinitions . . . . . . . . . . . . . . . . . . . 74
3.2.2 TheStatusQuoforMobility-InducedLink-LevelDynamics 74
3.3 Impact of User Availability on Link-Level Dynamics: Model and
Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
3.3.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . 79
3.3.2 UserAvailabilityComesintoPicture. . . . . . . . . . . . . 80
3.3.3 AnalysisofLink-LevelDynamics . . . . . . . . . . . . . . 81
3.3.3.1 Transfer-TimeDistributionandMeanInter-transfer
Time . . . . . . . . . . . . . . . . . . . . . . . . 81
3.3.3.2 Inter-transferTimeDistribution . . . . . . . . . . 83
3.4 Impact of User Availability on Link-Level Dynamics: Simulation
Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
3.5 DiscussionandConclusion . . . . . . . . . . . . . . . . . . . . . . 91
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
4 Discovering and Predicting Temporal Patterns of WiFi-Interactive So-
cialPopulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
XiangLi,Yi-QingZhang,andAthanasiosV.Vasilakos
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
4.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
4.3 PairwiseInteractivePatternsofTemporalContactsandReachability 104
4.4 Concurrent Interactive Patterns of Event Interactions and Temporal
TransmissionGraphs . . . . . . . . . . . . . . . . . . . . . . . . . 108
4.5 TemporalDegreesandHubs:RankingandPredictio . . . . . . . . 112
4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
5 BehavioralandStructuralAnalysisofMobileCloudOpportunisticNet-
works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Anh-DungNguyen,PatrickSenac,andMichelDiaz
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
5.2 UnderstandingandModelingOpportunisticNetworks . . . . . . . 126
5.2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 126
5.2.2 RelatedWorks . . . . . . . . . . . . . . . . . . . . . . . . 127
5.2.3 CharacterizingandModelingHumanMobility . . . . . . . 128
5.2.3.1 STEPS . . . . . . . . . . . . . . . . . . . . . . . 129
5.2.3.2 TheUnderlyingMarkovChain . . . . . . . . . . 130
