Preface |
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xv | |
Acknowledgments |
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xxi | |
Contributors |
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xxiii | |
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PART I CDN AND MEDIA STREAMING BASICS |
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1 | (158) |
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1 Cloud-Based Content Delivery and Streaming |
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3 | (30) |
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3 | (2) |
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5 | (5) |
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10 | (11) |
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21 | (7) |
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28 | (1) |
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29 | (4) |
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29 | (4) |
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2 Live Streaming Ecosystems |
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33 | (18) |
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33 | (1) |
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2.2 Live Streaming Pre-Evolution |
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34 | (1) |
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2.3 Live, Linear, Nonlinear |
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35 | (2) |
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37 | (1) |
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2.5 Related Network Models |
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38 | (5) |
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2.6 Streaming Protocol Success |
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43 | (1) |
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2.7 Platform Divergence and Codec Convergence |
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44 | (1) |
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2.8 Adaptive Bitrate (ABR) Streaming |
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45 | (3) |
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2.9 Internet Radio and HTTP |
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48 | (1) |
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48 | (3) |
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49 | (2) |
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3 Practical Systems for Live Streaming |
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51 | (20) |
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51 | (1) |
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3.2 Common Concepts in Live Streaming |
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52 | (4) |
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56 | (13) |
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69 | (2) |
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70 | (1) |
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4 Efficiency of Caching and Content Delivery in Broadband Access Networks |
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71 | (20) |
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71 | (2) |
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4.2 Options and Properties for Web Caching |
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73 | (2) |
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4.3 Zipf Laws for Requests to Popular Content |
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75 | (1) |
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4.4 Efficiency and Performance Modeling for Caches |
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76 | (2) |
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4.5 Effect of Replacement Strategies on Cache Hit Rates |
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78 | (3) |
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4.6 Replacement Methods Based on Request Statistics |
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81 | (3) |
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4.7 Global CDN and P2P Overlays for Content Delivery |
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84 | (2) |
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4.8 Summary and Conclusion |
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86 | (5) |
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87 | (1) |
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87 | (4) |
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5 Anycast Request Routing for Content Delivery Networks |
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91 | (28) |
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91 | (2) |
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5.2 CDN Request Routing: An Overview |
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93 | (3) |
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5.3 A Practical Load-Aware IP Anycast CDN |
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96 | (2) |
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98 | (4) |
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102 | (5) |
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107 | (7) |
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5.7 Discussion and Open Questions |
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114 | (2) |
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116 | (3) |
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116 | (3) |
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6 Cloud-Based Content Delivery to Home Ecosystems |
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119 | (22) |
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119 | (1) |
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6.2 Bringing Cloud Services to Home: State of the Art |
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120 | (3) |
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6.3 Virtualizing the Access Network Infrastructure |
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123 | (7) |
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6.4 Visualization for Cloud Service Delivery to Home |
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130 | (7) |
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137 | (1) |
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6.6 Summary and Conclusion |
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137 | (4) |
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137 | (1) |
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138 | (3) |
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141 | (18) |
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141 | (1) |
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7.2 Mobile Broadband Architecture |
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142 | (1) |
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7.3 Video Streaming Protocols |
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143 | (3) |
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7.4 Video Optimization Services |
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146 | (3) |
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149 | (2) |
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7.6 Cloud-Based Video Streaming |
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151 | (3) |
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7.7 Future Research Directions |
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154 | (5) |
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156 | (1) |
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156 | (3) |
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PART II CDN PERFORMANCE MANAGEMENT AND OPTIMIZATION |
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159 | (146) |
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8 CDN Analytics: A Primer |
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161 | (18) |
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161 | (1) |
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162 | (1) |
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162 | (7) |
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8.4 What about Business Intelligence? |
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169 | (2) |
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8.5 Measuring Stateless Delivery |
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171 | (2) |
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173 | (1) |
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174 | (1) |
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8.8 Recent Trends in CDN Analytics |
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175 | (1) |
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176 | (3) |
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176 | (3) |
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179 | (24) |
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179 | (1) |
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9.2 Basics on Mathematical Modeling and Optimization |
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180 | (2) |
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9.3 Video-on-Demand Applications |
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182 | (3) |
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9.4 Optimization Problems in Content Delivery and VoD Services |
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185 | (13) |
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9.5 Visionary Thoughts for Practitioners |
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198 | (1) |
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9.6 Future Research Directions |
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198 | (1) |
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199 | (4) |
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200 | (1) |
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200 | (3) |
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10 Analyzing Content Delivery Networks |
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203 | (16) |
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203 | (1) |
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204 | (1) |
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205 | (1) |
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206 | (6) |
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10.5 Performance Evaluation |
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212 | (4) |
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216 | (3) |
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216 | (3) |
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11 Multisource Stream Aggregation in the Cloud |
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219 | (24) |
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219 | (2) |
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221 | (1) |
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11.3 Background and Related Work |
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222 | (2) |
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11.4 The Substream Method in the Cloud |
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224 | (2) |
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11.5 Stream Aggregation in the Cloud |
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226 | (2) |
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228 | (3) |
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231 | (5) |
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11.8 Visionary Thoughts for Practitioners |
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236 | (2) |
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11.9 Future Research Directions |
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238 | (1) |
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239 | (4) |
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239 | (4) |
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12 Beyond CDN: Content Processing At the Edge of the Cloud |
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243 | (16) |
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243 | (1) |
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12.2 Existing Content Delivery Platforms |
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244 | (3) |
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12.3 Comparison of Existing Content Delivery Platforms |
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247 | (4) |
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12.4 An Edge Cloud-Based Model |
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251 | (4) |
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12.5 Results and Insights |
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255 | (1) |
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12.6 Future Research Directions |
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256 | (1) |
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257 | (2) |
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257 | (2) |
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13 Dynamic Reconfiguration for Adaptive Streaming |
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259 | (14) |
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259 | (1) |
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13.2 Background and Related Work |
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260 | (2) |
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13.3 Dynamic Server Deployment |
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262 | (1) |
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13.4 From Content Delivery to Streaming |
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263 | (4) |
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13.5 Future Research Directions |
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267 | (2) |
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269 | (4) |
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269 | (1) |
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269 | (4) |
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14 Mining Distributed Data Streams on Content Delivery Networks |
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273 | (16) |
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273 | (2) |
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14.2 Background and Related Work |
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275 | (2) |
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14.3 A Hybrid Multidomain Architecture |
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277 | (4) |
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14.4 A Prototype for Stream Mining in a CDN |
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281 | (4) |
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14.5 Visionary Thoughts for Practitioners |
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285 | (1) |
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14.6 Future Research Directions |
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285 | (1) |
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286 | (3) |
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286 | (3) |
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289 | (16) |
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289 | (1) |
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15.2 Capacity Planning Process |
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290 | (5) |
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15.3 Undertaking the Capacity Planning Process |
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295 | (5) |
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15.4 CDN Capacity Planning Case Study |
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300 | (2) |
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15.5 Recent Developments and Challenges |
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302 | (1) |
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15.6 Summary and Conclusion |
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303 | (2) |
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303 | (2) |
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PART III CASE STUDIES AND NEXT GENERATION CDNs |
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305 | (160) |
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16 Overlay Networks: An Akamai Perspective |
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307 | (22) |
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307 | (2) |
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309 | (5) |
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314 | (4) |
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318 | (5) |
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323 | (2) |
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325 | (4) |
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326 | (3) |
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17 Next-Generation CDNs: A CoBlitz Perspective |
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329 | (24) |
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329 | (2) |
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331 | (1) |
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332 | (1) |
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333 | (2) |
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335 | (2) |
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337 | (6) |
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17.7 CoBlitz Commercialization |
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343 | (2) |
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17.8 Implications of HTTP Adaptive Streaming |
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345 | (2) |
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17.9 CoBlitz Commercialization Lessons |
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347 | (1) |
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17.10 CDN Industry Directions |
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348 | (5) |
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349 | (1) |
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349 | (4) |
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18 Content Delivery in China: A ChinaCache Perspective |
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353 | (16) |
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353 | (3) |
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18.2 Content-Aware Network Services in China |
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356 | (9) |
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18.3 Directions for Future CDN Research and Trends in China |
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365 | (1) |
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366 | (3) |
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366 | (3) |
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19 PlatonTV: A Scientific High Definition Content Delivery Platform |
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369 | (16) |
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369 | (2) |
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19.2 Background and Related Work |
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371 | (1) |
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19.3 PlatonTV Architecture |
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372 | (2) |
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374 | (2) |
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19.5 Content Distribution and Management |
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376 | (3) |
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379 | (2) |
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19.7 Availability and Reliability |
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381 | (1) |
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19.8 Visionary Thoughts for Practitioners |
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382 | (1) |
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19.9 Future Research Directions |
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383 | (1) |
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383 | (2) |
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383 | (1) |
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384 | (1) |
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20 CacheCast: A Single-Source Multiple-Destination Caching Mechanism |
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385 | (28) |
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385 | (2) |
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387 | (1) |
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388 | (1) |
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20.4 Background on Multidestination Traffic |
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389 | (2) |
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391 | (5) |
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20.6 CacheCast Efficiency |
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396 | (3) |
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20.7 CacheCast Applications |
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399 | (8) |
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20.8 Visionary Thoughts for Practitioners |
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407 | (2) |
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20.9 Future Research Directions |
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409 | (1) |
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409 | (4) |
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410 | (1) |
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410 | (3) |
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21 Content Replication and Delivery in Information-Centric Networks |
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413 | (18) |
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413 | (1) |
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414 | (2) |
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21.3 Framework for Information Replication in ICN |
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416 | (7) |
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21.4 Performance Evaluation |
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423 | (3) |
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21.5 Future Research Directions |
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426 | (1) |
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426 | (5) |
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427 | (1) |
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427 | (4) |
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22 Robust Content Broadcasting in Vehicular Networks |
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431 | (18) |
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431 | (1) |
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432 | (1) |
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22.3 Forward Error Correction Techniques |
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433 | (1) |
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22.4 A Robust Broadcast-Based Content Delivery System |
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434 | (2) |
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22.5 CDS Simulation in NS-3 |
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436 | (1) |
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22.6 Performance Evaluation |
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437 | (7) |
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22.7 Future Research Trends |
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444 | (2) |
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22.8 Summary and Conclusion |
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446 | (3) |
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447 | (1) |
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447 | (2) |
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23 On the Impact of Online Social Networks in Content Delivery |
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449 | (16) |
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449 | (1) |
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23.2 Online Social Networks Background |
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450 | (3) |
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23.3 Characterization of Social Cascades |
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453 | (3) |
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23.4 Online Social Network Measurements |
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456 | (2) |
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458 | (1) |
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23.6 Future Research Directions |
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459 | (2) |
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461 | (4) |
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461 | (1) |
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461 | (4) |
Index |
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465 | |