Optimal Resource Allocation for Distributed Video Communication © 2014 by Taylor & Francis Group, LLC K13485_FM.indd 1 5/24/13 11:28 AM Multimedia Computing, Communication and Intelligence Series Editors: Chang Wen Chen and Shiguo Lian Effective Surveillance for Homeland Security: Balancing Technology and Social Issues Edited by Francesco Flammini, Roberto Setola, and Giorgio Franceschetti ISBN: 978-1-4398-8324-2 Music Emotion Recognition Yi-Hsuan Yang and Homer H. Chen ISBN: 978-1-4398-5046-6 Optimal Resource Allocation for Distributed Video and Multimedia Communications Yifeng He, Ling Guan, and Wenwu Zhu ISBN: 978-1-4398-7514-8 TV Content Analysis: Techniques and Applications Edited by Yiannis Kompatsiaris, Bernard Merialdo, and Shiguo Lian ISBN: 978-1-4398-5560-7 © 2014 by Taylor & Francis Group, LLC K13485_FM.indd 2 5/24/13 11:28 AM Optimal Resource Allocation for Distributed Video Communication Yifeng He s Ling Guan s Wenwu Zhu © 2014 by Taylor & Francis Group, LLC K13485_FM.indd 3 5/24/13 11:28 AM CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2014 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Version Date: 20130507 International Standard Book Number-13: 978-1-4398-7516-2 (eBook - PDF) This book contains information obtained from authentic and highly regarded sources. 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Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com © 2014 by Taylor & Francis Group, LLC CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2014 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed on acid-free paper Version Date: 20130507 International Standard Book Number-13: 978-1-4398-7514-8 (Hardback) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. 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Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com © 2014 by Taylor & Francis Group, LLC K13485_FM.indd 4 5/24/13 11:28 AM Contents List of Figures ix List of Tables xiii Preface xv 1 Introduction 1 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Technical Challenges in Distributed Video Communications . 3 1.3 Recent Advances in Optimal Resource Allocation for Dis- tributed Video Communications . . . . . . . . . . . . . . . . 4 1.3.1 Optimal Resource Allocation in P2P Streaming Systems 4 1.3.1.1 P2P Live Streaming Systems . . . . . . . . . 5 1.3.1.2 P2P VoD Streaming Systems . . . . . . . . . 6 1.3.2 Optimal Resource Allocation for Video Streaming over Wireless Ad Hoc Networks . . . . . . . . . . . . . . . 8 1.3.3 OptimalResourceAllocationforWirelessVisualSensor Networks . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.4 Overview of the Book . . . . . . . . . . . . . . . . . . . . . . 11 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2 Optimized Resource Allocation for Scalable Video Commu- nications 17 2.1 Network-Adaptive Resource Allocation for Scalable Video Streaming over the Internet . . . . . . . . . . . . . . . . . . . 18 2.2 QoS-Adaptive Resource Allocation for Scalable Video Trans- mission over Cellular Networks . . . . . . . . . . . . . . . . . 24 2.2.1 Hybrid UEP and Delay-Constrained ARQ for Scalable Video Delivery . . . . . . . . . . . . . . . . . . . . . . 28 2.2.2 Distortion-Minimized Resource Allocation . . . . . . . 30 2.2.3 Power-MinimizedResource Allocation . . . . . . . . . 32 2.3 Power-MinimizedJointPowerControlandResourceAllocation for Video Communications over Wireless Channels . . . . . . 35 2.3.1 Power-Rate Relationship and Power-Minimized Rate Allocation for a Single User . . . . . . . . . . . . . . . 37 2.3.2 Power-RateRelationshipandPower-MinimizationRate Allocation for a Group of Users . . . . . . . . . . . . . 39 v © 2014 by Taylor & Francis Group, LLC vi Contents 2.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 3 Optimal Resource Allocation for P2P Streaming Systems 49 3.1 Overview of P2P Streaming Systems . . . . . . . . . . . . . . 50 3.1.1 P2P Live Streaming Systems . . . . . . . . . . . . . . 51 3.1.2 P2P VoD Systems . . . . . . . . . . . . . . . . . . . . 52 3.2 Distributed Throughput Maximization for Scalable P2P VoD systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 3.2.1 Throughput Maximization in Buffer-Forwarding P2P VoD Systems . . . . . . . . . . . . . . . . . . . . . . . 55 3.2.1.1 Problem Formulation . . . . . . . . . . . . . 55 3.2.1.2 Distributed Solution . . . . . . . . . . . . . . 59 3.2.1.3 Simulation Results . . . . . . . . . . . . . . . 61 3.2.2 Throughput Maximization in Hybrid-Forwarding P2P VoD Systems . . . . . . . . . . . . . . . . . . . . . . . 65 3.2.2.1 Problem Formulation . . . . . . . . . . . . . 66 3.2.2.2 Simulation Results . . . . . . . . . . . . . . . 69 3.3 Streaming Capacity for P2P VoD systems . . . . . . . . . . . 72 3.3.1 Streaming Capacity for an Independent-Channel P2P VoD System. . . . . . . . . . . . . . . . . . . . . . . . 74 3.3.2 StreamingCapacityforaCorrelated-ChannelP2PVoD System . . . . . . . . . . . . . . . . . . . . . . . . . . 77 3.3.2.1 Optimization of Server Upload Allocation among Channels . . . . . . . . . . . . . . . . 77 3.3.2.2 Cross-Channel Sharing of Peer Upload Band- width . . . . . . . . . . . . . . . . . . . . . . 79 3.3.3 Simulation Results . . . . . . . . . . . . . . . . . . . . 80 3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4 Prefetching Scheme and Substream Allocation in P2P VoD Applications 89 4.1 Optimal Prefetching Scheme in P2P VoD Applications with Guided Seeks . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 4.1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . 90 4.1.2 Seeking Statistics Aggregation . . . . . . . . . . . . . 93 4.1.2.1 Intuitive Approach. . . . . . . . . . . . . . . 95 4.1.2.2 The Proposed Hybrid Sketches . . . . . . . . 95 4.1.2.3 Estimation of Segment Access Probability. . 97 4.1.3 Optimal Prefetching Scheme . . . . . . . . . . . . . . 97 4.1.3.1 The Optimal Prefetching Scheme. . . . . . . 97 4.1.3.2 The Optimal Cache Replacement Policy . . . 102 4.1.4 Simulation Results . . . . . . . . . . . . . . . . . . . . 102 © 2014 by Taylor & Francis Group, LLC Contents vii 4.1.4.1 Performance Evaluation of Seeking Statistics Aggregation . . . . . . . . . . . . . . . . . . 103 4.1.4.2 Performance Evaluation of the Prefetching Scheme . . . . . . . . . . . . . . . . . . . . . 106 4.1.5 Practical Issues . . . . . . . . . . . . . . . . . . . . . . 110 4.2 Optimization of Substream Allocation in Layered P2P Appli- cations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 4.2.1 Optimal Substream Allocation Scheme . . . . . . . . . 112 4.2.1.1 Single-File system . . . . . . . . . . . . . . . 112 4.2.1.2 Multi-File system . . . . . . . . . . . . . . . 114 4.2.2 Evolution of Video Quality and Peer Population . . . 115 4.2.3 Simulation Results . . . . . . . . . . . . . . . . . . . . 116 4.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 5 Video Streaming over Wireless Ad Hoc Networks 123 5.1 System Models . . . . . . . . . . . . . . . . . . . . . . . . . . 124 5.1.1 Video Distortion Model . . . . . . . . . . . . . . . . . 124 5.1.2 Network Model . . . . . . . . . . . . . . . . . . . . . . 125 5.1.3 Packet Loss Model . . . . . . . . . . . . . . . . . . . . 125 5.2 Optimized Video Unicasting over Wireless Ad Hoc Networks 127 5.2.1 Problem Formulation and Distributed Solution . . . . 128 5.2.1.1 Problem Formulation . . . . . . . . . . . . . 128 5.2.1.2 Distributed Solution . . . . . . . . . . . . . . 129 5.2.2 Simulation results . . . . . . . . . . . . . . . . . . . . 130 5.3 Optimized Video Multicasting over FDMA Wireless Ad Hoc Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 5.3.1 Problem Formulation and Distributed Solution . . . . 133 5.3.1.1 Problem Formulation . . . . . . . . . . . . . 133 5.3.1.2 Distributed Solution . . . . . . . . . . . . . . 134 5.3.2 Simulation Results . . . . . . . . . . . . . . . . . . . . 136 5.4 Distributed Cross-Layer Optimization for Video Multicasting over CDMA Wireless Ad Hoc Networks . . . . . . . . . . . . 139 5.4.1 Problem Formulation . . . . . . . . . . . . . . . . . . 140 5.4.2 Distributed Algorithm . . . . . . . . . . . . . . . . . . 141 5.4.2.1 First-Layer Decomposition . . . . . . . . . . 141 5.4.2.2 Second-Layer Decomposition . . . . . . . . . 142 5.4.3 Simulation Results . . . . . . . . . . . . . . . . . . . . 145 5.5 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . 154 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 6 OptimalResourceAllocationforWirelessVisualSensorNet- works 157 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 6.2 System Models . . . . . . . . . . . . . . . . . . . . . . . . . . 159 © 2014 by Taylor & Francis Group, LLC viii Contents 6.2.1 Network Graph . . . . . . . . . . . . . . . . . . . . . . 159 6.2.2 Channel Error Model . . . . . . . . . . . . . . . . . . 160 6.2.3 Power Consumption Model . . . . . . . . . . . . . . . 161 6.2.4 Network Lifetime . . . . . . . . . . . . . . . . . . . . . 162 6.3 Achievable Maximum Network Lifetime . . . . . . . . . . . . 162 6.3.1 Problem Formulation . . . . . . . . . . . . . . . . . . 163 6.3.2 Distributed Algorithm . . . . . . . . . . . . . . . . . . 165 6.3.3 Simulation Results . . . . . . . . . . . . . . . . . . . . 167 6.4 Maximum Network Lifetime for Large-Delay Applications . . 171 6.4.1 Problem Formulation and Solution . . . . . . . . . . . 171 6.4.2 Simulation Results . . . . . . . . . . . . . . . . . . . . 172 6.5 Maximum Network Lifetime for Small-Delay Applications . . 175 6.5.1 With FEC. . . . . . . . . . . . . . . . . . . . . . . . . 175 6.5.1.1 Problem Formulation and Solution . . . . . . 175 6.5.1.2 Simulation Results . . . . . . . . . . . . . . . 177 6.5.2 Without FEC . . . . . . . . . . . . . . . . . . . . . . . 177 6.5.2.1 Transmission Distortion . . . . . . . . . . . . 180 6.5.2.2 TradeoffbetweenMaximumNetworkLifetime and Video Quality . . . . . . . . . . . . . . . 181 6.6 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . 182 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Index 187 © 2014 by Taylor & Francis Group, LLC
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