Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Fog for 5G and IoT / / edited by Mung Chiang, Bharath Balasubramanian, Flavio Bonomi
| Fog for 5G and IoT / / edited by Mung Chiang, Bharath Balasubramanian, Flavio Bonomi |
| Autore | Chiang Mung |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, New Jersey, USA : , : John Wiley & Sons Inc., , 2017 |
| Descrizione fisica | 1 online resource (307 pages) : illustrations |
| Disciplina | 004.67/82 |
| Collana | Information and communication technology series |
| Soggetto topico |
Electronic data processing - Distributed processing
Distributed shared memory Storage area networks (Computer networks) Mobile computing Internet of things Cloud computing |
| ISBN |
1-119-18717-6
1-119-18715-X 1-119-18720-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
-- CONTRIBUTORS xi / /Introduction 1 /Bharath Balasubramanian, Mung Chiang, and Flavio Bonomi / /I.1 Summary of Chapters 5 / /I.2 Acknowledgments 7 / /References 8 / /I COMMUNICATION AND MANAGEMENT OF FOG 11 / /1 ParaDrop: An Edge Computing Platform in Home Gateways 13 /Suman Banerjee, Peng Liu, Ashish Patro, and Dale Willis / /1.1 Introduction 13 / /1.1.1 Enabling Multitenant Wireless Gateways and Applications through ParaDrop 14 / /1.1.2 ParaDrop Capabilities 15 / /1.2 Implementing Services for the ParaDrop Platform 17 / /1.3 Develop Services for ParaDrop 19 / /1.3.1 A Security Camera Service Using ParaDrop 19 / /1.3.2 An Environmental Sensor Service Using ParaDrop 22 / /References 23 / /2 Mind Your Own Bandwidth 24 /Carlee Joe-Wong, Sangtae Ha, Zhenming Liu, Felix Ming Fai Wong, and Mung Chiang / /2.1 Introduction 24 / /2.1.1 Leveraging the Fog 25 / /2.1.2 A Home Solution to a Home Problem 25 / /2.2 Related Work 28 / /2.3 Credit Distribution and Optimal Spending 28 / /2.3.1 Credit Distribution 29 / /2.3.2 Optimal Credit Spending 31 / /2.4 An Online Bandwidth Allocation Algorithm 32 / /2.4.1 Estimating Other Gateways' Spending 32 / /2.4.2 Online Spending Decisions and App Prioritization 34 / /2.5 Design and Implementation 35 / /2.5.1 Traffic and Device Classification 37 / /2.5.2 Rate Limiting Engine 37 / /2.5.3 Traffic Prioritization Engine 38 / /2.6 Experimental Results 39 / /2.6.1 Rate Limiting 39 / /2.6.2 Traffic Prioritization 41 / /2.7 Gateway Sharing Results 41 / /2.8 Concluding Remarks 45 / /Acknowledgments 46 / /Appendix 2.A 46 / /2.A.1 Proof of Lemma 2.1 46 / /2.A.2 Proof of Lemma 2.2 46 / /2.A.3 Proof of Proposition 2.1 47 / /2.A.4 Proof of Proposition 2.2 48 / /2.A.5 Proof of Proposition 2.3 49 / /2.A.6 Proof of Proposition 2.4 49 / /References 50 / /3 Socially-Aware Cooperative D2D and D4D Communications toward Fog Networking 52 /Xu Chen, Junshan Zhang, and Satyajayant Misra / /3.1 Introduction 52 / /3.1.1 From Social Trust and Social Reciprocity to D2D Cooperation 54 / /3.1.2 Smart Grid: An IoT Case for Socially-Aware Cooperative D2D and D4D Communications 55 / /3.1.3 Summary of Main Results 57 / /3.2 Related Work 58 / /3.3 System Model 59 / /3.3.1 Physical (Communication) Graph Model 60 / /3.3.2 Social Graph Model 61 / /3.4 Socially-Aware Cooperative D2D and D4D Communications toward Fog Networking 62 / /3.4.1 Social Trust-Based Relay Selection 63 / /3.4.2 Social Reciprocity-Based Relay Selection 63 / /3.4.3 Social Trust and Social Reciprocity-Based Relay Selection 68 / /3.5 Network Assisted Relay Selection Mechanism 69 / /3.5.1 Reciprocal Relay Selection Cycle Finding 69 / /3.5.2 NARS Mechanism 70 / /3.5.3 Properties of NARS Mechanism 73 / /3.6 Simulations 75 / /3.6.1 Erdos / Renyi Social Graph 76 / /3.6.2 Real Trace Based Social Graph 78 / /3.7 Conclusion 82 / /Acknowledgments 82 / /References 83 / /4 You Deserve Better Properties (From Your Smart Devices) 86 /Steven Y. Ko / /4.1 Why We Need to Provide Better Properties 86 / /4.2 Where We Need to Provide Better Properties 87 / /4.3 What Properties We Need to Provide and How 88 / /4.3.1 Transparency 88 / /4.3.2 Predictable Performance 93 / /4.3.3 Openness 99 / /4.4 Conclusions 102 / /Acknowledgment 102 / /References 103 / /II STORAGE AND COMPUTATION IN FOG 107 / /5 Distributed Caching for Enhancing Communications Efficiency 109 /A. Salman Avestimehr and Andreas F. Molisch / /5.1 Introduction 109 / /5.2 Femtocaching 111 / /5.2.1 System Model 111 / /5.2.2 Adaptive Streaming from Helper Stations 114 / /5.3 User-Caching 115 / /5.3.1 Cluster-Based Caching and D2D Communications 115 / /5.3.2 IT LinQ-Based Caching and Communications 118 / /5.3.3 Coded Multicast 126 / /5.4 Conclusions and Outlook 130 / /References 131 / /6 Wireless Video Fog: Collaborative Live Streaming with Error Recovery 133 /Bo Zhang, Zhi Liu, and S.-H. Gary Chan / /6.1 Introduction 133 / /6.2 Related Work 136 / /6.3 System Operation and Network Model 138 / /6.4 Problem Formulation and Complexity 140 / /6.4.1 NC Packet Selection Optimization 140 / /6.4.2 Broadcaster Selection Optimization 143 / /6.4.3 Complexity Analysis 144 / /6.5 VBCR: A Distributed Heuristic for Live Video with Cooperative Recovery 144 / /6.5.1 Initial Information Exchange 145 / /6.5.2 Cooperative Recovery 145 / /6.5.3 Updated Information Exchange 147 / /6.5.4 Video Packet Forwarding 147 / /6.6 Illustrative Simulation Results 150 / /6.7 Concluding Remarks 156 / /References 156 / /7 Elastic Mobile Device Clouds: Leveraging Mobile Devices to Provide Cloud Computing Services at the Edge 159 /Karim Habak, Cong Shi, Ellen W. Zegura, Khaled A. Harras, and Mostafa Ammar / /7.1 Introduction 159 / /7.2 Design Space with Examples 161 / /7.2.1 Mont-Blanc 162 / /7.2.2 Computing while Charging 163 / /7.2.3 FemtoCloud 164 / /7.2.4 Serendipity 166 / /7.3 FemtoCloud Performance Evaluation 168 / /7.3.1 Experimental Setup 168 / /7.3.2 FemtoCloud Simulation Results 169 / /7.3.3 FemtoCloud Prototype Evaluation 173 / /7.4 Serendipity Performance Evaluation 175 / /7.4.1 Experimental Setup 175 / /7.4.2 Serendipity's Performance Benefits 176 / /7.4.3 Impact of Network Environment 179 / /7.4.4 The Impact of the Job Properties 182 / /7.5 Challenges 186 / /References 186 / /III APPLICATIONS OF FOG 189 / /8 The Role of Fog Computing in the Future of the Automobile 191 /Flavio Bonomi, Stefan Poledna, and Wilfried Steiner / /8.1 Introduction 191 / /8.2 Current Automobile Electronic Architectures 193 / /8.3 Future Challenges of Automotive E/E Architectures and Solution Strategies 195 / /8.4 Future Automobiles as Fog Nodes on Wheels 200 / /8.5 Deterministic FOG Nodes on Wheels Through Real-Time Computing and Time-Triggered Technologies /203 / /8.5.1 Deterministic Fog Node Addressing the Scalability Challenge through Virtualization 203 / /8.5.2 Deterministic Fog Node Addressing the Connectivity and Security Challenges 204 / /8.5.3 Emerging Use Case of Deterministic Fog Nodes in Automotive Applications - Vehicle-Wide /Virtualization 206 / /8.6 Conclusion 209 / /References 209 / /9 Geographic Addressing for Field Networks 211 /Robert J. Hall / /9.1 Introduction 211 / /9.1.1 Field Networking 211 / /9.1.2 Challenges of Field Networking 212 / /9.2 Geographic Addressing 214 / /9.3 SAGP: Wireless GA in the Field 215 / /9.3.1 SAGP Processing 216 / /9.3.2 SAGP Retransmission Heuristics 217 / /9.3.3 Example of SAGP Packet Propagation 218 / /9.3.4 Followcast: Efficient SAGP Streaming 219 / /9.3.5 Meeting the Challenges 220 / /9.4 Georouting: Extending GA to the Cloud 221 / /9.5 SGAF: A Multi-Tiered Architecture for Large-Scale GA 222 / /9.5.1 Bridging Between Tiers 223 / /9.5.2 Hybrid Security Architecture 225 / /9.6 The AT&T Labs Geocast System 225 / /9.7 Two GA Applications 226 / /9.7.1 PSCommander 226 / /9.7.2 Geocast Games 230 / /9.8 Conclusions 232 / /References 232 / /10 Distributed Online Learning and Stream Processing for a Smarter Planet 234 /Deepak S.
Turaga and Mihaela van der Schaar / /10.1 Introduction: Smarter Planet 234 / /10.2 Illustrative Problem: Transportation 237 / /10.3 Stream Processing Characteristics 238 / /10.4 Distributed Stream Processing Systems 239 / /10.4.1 State of the Art 239 / /10.4.2 Stream Processing Systems 240 / /10.5 Distributed Online Learning Frameworks 244 / /10.5.1 State of the Art 244 / /10.5.2 Systematic Framework for Online Distributed Ensemble Learning 247 / /10.5.3 Online Learning of the Aggregation Weights 250 / /10.5.4 Collision Detection Application 254 / /10.6 What Lies Ahead 257 / /Acknowledgment 258 / /References 258 / /11 Securing the Internet of Things: Need for a New Paradigm and Fog Computing 261 /Tao Zhang, Yi Zheng, Raymond Zheng, and Helder Antunes / /11.1 Introduction 261 / /11.2 New IoT Security Challenges That Necessitate Fundamental Changes to the Existing Security /Paradigm 263 / /11.2.1 Many Things Will Have Long Life Spans but Constrained and Difficult-to-Upgrade Resources 264 / /11.2.2 Putting All IoT Devices Inside Firewalled Castles Will Become Infeasible or Impractical 264 / /11.2.3 Mission-Critical Systems Will Demand Minimal-Impact Incident Responses 265 / /11.2.4 The Need to Know the Security Status of a Vast Number of Devices 266 / /11.3 A New Security Paradigm for the Internet of Things 268 / /11.3.1 Help the Less Capable with Fog Computing 269 / /11.3.2 Scale Security Monitoring to Large Number of Devices with Crowd Attestation 272 / /11.3.3 Dynamic Risk / Benefit-Proportional Protection with Adaptive Immune Security 277 / /11.4 Summary 281 / /Acknowledgment 281 / /References 281 / /INDEX 285. |
| Record Nr. | UNINA-9910270903403321 |
Chiang Mung
|
||
| Hoboken, New Jersey, USA : , : John Wiley & Sons Inc., , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Fog for 5G and IoT / / edited by Mung Chiang, Bharath Balasubramanian, Flavio Bonomi
| Fog for 5G and IoT / / edited by Mung Chiang, Bharath Balasubramanian, Flavio Bonomi |
| Autore | Chiang Mung |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, New Jersey, USA : , : John Wiley & Sons Inc., , 2017 |
| Descrizione fisica | 1 online resource (307 pages) : illustrations |
| Disciplina | 004.67/82 |
| Collana | Information and communication technology series |
| Soggetto topico |
Electronic data processing - Distributed processing
Distributed shared memory Storage area networks (Computer networks) Mobile computing Internet of things Cloud computing |
| ISBN |
1-119-18717-6
1-119-18715-X 1-119-18720-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
-- CONTRIBUTORS xi / /Introduction 1 /Bharath Balasubramanian, Mung Chiang, and Flavio Bonomi / /I.1 Summary of Chapters 5 / /I.2 Acknowledgments 7 / /References 8 / /I COMMUNICATION AND MANAGEMENT OF FOG 11 / /1 ParaDrop: An Edge Computing Platform in Home Gateways 13 /Suman Banerjee, Peng Liu, Ashish Patro, and Dale Willis / /1.1 Introduction 13 / /1.1.1 Enabling Multitenant Wireless Gateways and Applications through ParaDrop 14 / /1.1.2 ParaDrop Capabilities 15 / /1.2 Implementing Services for the ParaDrop Platform 17 / /1.3 Develop Services for ParaDrop 19 / /1.3.1 A Security Camera Service Using ParaDrop 19 / /1.3.2 An Environmental Sensor Service Using ParaDrop 22 / /References 23 / /2 Mind Your Own Bandwidth 24 /Carlee Joe-Wong, Sangtae Ha, Zhenming Liu, Felix Ming Fai Wong, and Mung Chiang / /2.1 Introduction 24 / /2.1.1 Leveraging the Fog 25 / /2.1.2 A Home Solution to a Home Problem 25 / /2.2 Related Work 28 / /2.3 Credit Distribution and Optimal Spending 28 / /2.3.1 Credit Distribution 29 / /2.3.2 Optimal Credit Spending 31 / /2.4 An Online Bandwidth Allocation Algorithm 32 / /2.4.1 Estimating Other Gateways' Spending 32 / /2.4.2 Online Spending Decisions and App Prioritization 34 / /2.5 Design and Implementation 35 / /2.5.1 Traffic and Device Classification 37 / /2.5.2 Rate Limiting Engine 37 / /2.5.3 Traffic Prioritization Engine 38 / /2.6 Experimental Results 39 / /2.6.1 Rate Limiting 39 / /2.6.2 Traffic Prioritization 41 / /2.7 Gateway Sharing Results 41 / /2.8 Concluding Remarks 45 / /Acknowledgments 46 / /Appendix 2.A 46 / /2.A.1 Proof of Lemma 2.1 46 / /2.A.2 Proof of Lemma 2.2 46 / /2.A.3 Proof of Proposition 2.1 47 / /2.A.4 Proof of Proposition 2.2 48 / /2.A.5 Proof of Proposition 2.3 49 / /2.A.6 Proof of Proposition 2.4 49 / /References 50 / /3 Socially-Aware Cooperative D2D and D4D Communications toward Fog Networking 52 /Xu Chen, Junshan Zhang, and Satyajayant Misra / /3.1 Introduction 52 / /3.1.1 From Social Trust and Social Reciprocity to D2D Cooperation 54 / /3.1.2 Smart Grid: An IoT Case for Socially-Aware Cooperative D2D and D4D Communications 55 / /3.1.3 Summary of Main Results 57 / /3.2 Related Work 58 / /3.3 System Model 59 / /3.3.1 Physical (Communication) Graph Model 60 / /3.3.2 Social Graph Model 61 / /3.4 Socially-Aware Cooperative D2D and D4D Communications toward Fog Networking 62 / /3.4.1 Social Trust-Based Relay Selection 63 / /3.4.2 Social Reciprocity-Based Relay Selection 63 / /3.4.3 Social Trust and Social Reciprocity-Based Relay Selection 68 / /3.5 Network Assisted Relay Selection Mechanism 69 / /3.5.1 Reciprocal Relay Selection Cycle Finding 69 / /3.5.2 NARS Mechanism 70 / /3.5.3 Properties of NARS Mechanism 73 / /3.6 Simulations 75 / /3.6.1 Erdos / Renyi Social Graph 76 / /3.6.2 Real Trace Based Social Graph 78 / /3.7 Conclusion 82 / /Acknowledgments 82 / /References 83 / /4 You Deserve Better Properties (From Your Smart Devices) 86 /Steven Y. Ko / /4.1 Why We Need to Provide Better Properties 86 / /4.2 Where We Need to Provide Better Properties 87 / /4.3 What Properties We Need to Provide and How 88 / /4.3.1 Transparency 88 / /4.3.2 Predictable Performance 93 / /4.3.3 Openness 99 / /4.4 Conclusions 102 / /Acknowledgment 102 / /References 103 / /II STORAGE AND COMPUTATION IN FOG 107 / /5 Distributed Caching for Enhancing Communications Efficiency 109 /A. Salman Avestimehr and Andreas F. Molisch / /5.1 Introduction 109 / /5.2 Femtocaching 111 / /5.2.1 System Model 111 / /5.2.2 Adaptive Streaming from Helper Stations 114 / /5.3 User-Caching 115 / /5.3.1 Cluster-Based Caching and D2D Communications 115 / /5.3.2 IT LinQ-Based Caching and Communications 118 / /5.3.3 Coded Multicast 126 / /5.4 Conclusions and Outlook 130 / /References 131 / /6 Wireless Video Fog: Collaborative Live Streaming with Error Recovery 133 /Bo Zhang, Zhi Liu, and S.-H. Gary Chan / /6.1 Introduction 133 / /6.2 Related Work 136 / /6.3 System Operation and Network Model 138 / /6.4 Problem Formulation and Complexity 140 / /6.4.1 NC Packet Selection Optimization 140 / /6.4.2 Broadcaster Selection Optimization 143 / /6.4.3 Complexity Analysis 144 / /6.5 VBCR: A Distributed Heuristic for Live Video with Cooperative Recovery 144 / /6.5.1 Initial Information Exchange 145 / /6.5.2 Cooperative Recovery 145 / /6.5.3 Updated Information Exchange 147 / /6.5.4 Video Packet Forwarding 147 / /6.6 Illustrative Simulation Results 150 / /6.7 Concluding Remarks 156 / /References 156 / /7 Elastic Mobile Device Clouds: Leveraging Mobile Devices to Provide Cloud Computing Services at the Edge 159 /Karim Habak, Cong Shi, Ellen W. Zegura, Khaled A. Harras, and Mostafa Ammar / /7.1 Introduction 159 / /7.2 Design Space with Examples 161 / /7.2.1 Mont-Blanc 162 / /7.2.2 Computing while Charging 163 / /7.2.3 FemtoCloud 164 / /7.2.4 Serendipity 166 / /7.3 FemtoCloud Performance Evaluation 168 / /7.3.1 Experimental Setup 168 / /7.3.2 FemtoCloud Simulation Results 169 / /7.3.3 FemtoCloud Prototype Evaluation 173 / /7.4 Serendipity Performance Evaluation 175 / /7.4.1 Experimental Setup 175 / /7.4.2 Serendipity's Performance Benefits 176 / /7.4.3 Impact of Network Environment 179 / /7.4.4 The Impact of the Job Properties 182 / /7.5 Challenges 186 / /References 186 / /III APPLICATIONS OF FOG 189 / /8 The Role of Fog Computing in the Future of the Automobile 191 /Flavio Bonomi, Stefan Poledna, and Wilfried Steiner / /8.1 Introduction 191 / /8.2 Current Automobile Electronic Architectures 193 / /8.3 Future Challenges of Automotive E/E Architectures and Solution Strategies 195 / /8.4 Future Automobiles as Fog Nodes on Wheels 200 / /8.5 Deterministic FOG Nodes on Wheels Through Real-Time Computing and Time-Triggered Technologies /203 / /8.5.1 Deterministic Fog Node Addressing the Scalability Challenge through Virtualization 203 / /8.5.2 Deterministic Fog Node Addressing the Connectivity and Security Challenges 204 / /8.5.3 Emerging Use Case of Deterministic Fog Nodes in Automotive Applications - Vehicle-Wide /Virtualization 206 / /8.6 Conclusion 209 / /References 209 / /9 Geographic Addressing for Field Networks 211 /Robert J. Hall / /9.1 Introduction 211 / /9.1.1 Field Networking 211 / /9.1.2 Challenges of Field Networking 212 / /9.2 Geographic Addressing 214 / /9.3 SAGP: Wireless GA in the Field 215 / /9.3.1 SAGP Processing 216 / /9.3.2 SAGP Retransmission Heuristics 217 / /9.3.3 Example of SAGP Packet Propagation 218 / /9.3.4 Followcast: Efficient SAGP Streaming 219 / /9.3.5 Meeting the Challenges 220 / /9.4 Georouting: Extending GA to the Cloud 221 / /9.5 SGAF: A Multi-Tiered Architecture for Large-Scale GA 222 / /9.5.1 Bridging Between Tiers 223 / /9.5.2 Hybrid Security Architecture 225 / /9.6 The AT&T Labs Geocast System 225 / /9.7 Two GA Applications 226 / /9.7.1 PSCommander 226 / /9.7.2 Geocast Games 230 / /9.8 Conclusions 232 / /References 232 / /10 Distributed Online Learning and Stream Processing for a Smarter Planet 234 /Deepak S.
Turaga and Mihaela van der Schaar / /10.1 Introduction: Smarter Planet 234 / /10.2 Illustrative Problem: Transportation 237 / /10.3 Stream Processing Characteristics 238 / /10.4 Distributed Stream Processing Systems 239 / /10.4.1 State of the Art 239 / /10.4.2 Stream Processing Systems 240 / /10.5 Distributed Online Learning Frameworks 244 / /10.5.1 State of the Art 244 / /10.5.2 Systematic Framework for Online Distributed Ensemble Learning 247 / /10.5.3 Online Learning of the Aggregation Weights 250 / /10.5.4 Collision Detection Application 254 / /10.6 What Lies Ahead 257 / /Acknowledgment 258 / /References 258 / /11 Securing the Internet of Things: Need for a New Paradigm and Fog Computing 261 /Tao Zhang, Yi Zheng, Raymond Zheng, and Helder Antunes / /11.1 Introduction 261 / /11.2 New IoT Security Challenges That Necessitate Fundamental Changes to the Existing Security /Paradigm 263 / /11.2.1 Many Things Will Have Long Life Spans but Constrained and Difficult-to-Upgrade Resources 264 / /11.2.2 Putting All IoT Devices Inside Firewalled Castles Will Become Infeasible or Impractical 264 / /11.2.3 Mission-Critical Systems Will Demand Minimal-Impact Incident Responses 265 / /11.2.4 The Need to Know the Security Status of a Vast Number of Devices 266 / /11.3 A New Security Paradigm for the Internet of Things 268 / /11.3.1 Help the Less Capable with Fog Computing 269 / /11.3.2 Scale Security Monitoring to Large Number of Devices with Crowd Attestation 272 / /11.3.3 Dynamic Risk / Benefit-Proportional Protection with Adaptive Immune Security 277 / /11.4 Summary 281 / /Acknowledgment 281 / /References 281 / /INDEX 285. |
| Record Nr. | UNINA-9910830457203321 |
|
Chiang Mung
|
||
| Hoboken, New Jersey, USA : , : John Wiley & Sons Inc., , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Proceedings of the 2009 Mobihoc S3 workshop on MobiHoc S3
| Proceedings of the 2009 Mobihoc S3 workshop on MobiHoc S3 |
| Autore | Chiang Mung |
| Pubbl/distr/stampa | [Place of publication not identified], : Association for Computing Machinery, 2009 |
| Descrizione fisica | 1 online resource (54 p.;) |
| Collana | ACM Conferences |
| Soggetto topico | Information Technology - Computer Science (Hardware & Networks) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | MobiHoc S3 '09 |
| Record Nr. | UNINA-9910510509203321 |
|
Chiang Mung
|
||
| [Place of publication not identified], : Association for Computing Machinery, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||