Fog and fogonomics : challenges and practices of fog computing, communication, networking, strategy, and economics /: challenges and practices of fog computing, communication, networking, strategy, and economics. (2020)

• Record Type: Book
• Further Information: Note: Edited by Yang Yang, Jianwei Huang, Tao Zhang, Joe Weinman.
• Editors: Yang, Yang; Huang, Jianwei; Zhang, Tao; Weinman, Joe, 1958-
• Contents: List of Contributors xvii Preface xxi 1 Fog Computing and Fogonomics 1; Yang Yang, Jianwei Huang, Tao Zhang, and Joe Weinman 2 Collaborative Mechanism for Hybrid Fog-Cloud Scenarios 7; Xavi Masip, Eva Marín, Jordi Garcia, and Sergi Sànchez 2.1 The Collaborative Scenario 7 2.1.1 The F2C Model 11 2.1.1.1 The Layering Architecture 13 2.1.1.2 The Fog Node 14 2.1.1.3 F2C as a Service 16 2.1.2 The F2C Control Architecture 19 2.1.2.1 Hierarchical Architecture 20 2.1.2.2 Main Functional Blocks 24 2.1.2.3 Managing Control Data 25 2.1.2.4 Sharing Resources 26 2.2 Benefits and Applicability 28 2.3 The Challenges 29 2.3.1 Research Challenges 30 2.3.1.1 What a Resource is 30 2.3.1.2 Categorization 30 2.3.1.3 Identification 31 2.3.1.4 Clustering 33 2.3.1.5 Resources Discovery 33 2.3.1.6 Resource Allocation 34 2.3.1.7 Reliability 35 2.3.1.8 QoS 36 2.3.1.9 Security 36 2.3.2 Industry Challenges 37 2.3.2.1 What an F2C Provider Should Be? 38 2.3.2.2 Shall Cloud/Fog Providers Communicate with Each Other 38 2.3.2.3 How Multifog/Cloud Access is Managed 39 2.3.3 Business Challenges 40 2.4 Ongoing Efforts 41 2.4.1 ECC 41 2.4.2 mF2C 42 2.4.3 MEC 42 2.4.4 OEC 44 2.4.5 OFC 44 2.5 Handling Data in Coordinated Scenarios 45 2.5.1 The New Data 46 2.5.2 The Life Cycle of Data 48 2.5.3 F2C Data Management 49 2.5.3.1 Data Collection 49 2.5.3.2 Data Storage 51 2.5.3.3 Data Processing 52 2.6 The Coming Future 52 Acknowledgments 54 References 54 3 Computation Offloading Game for Fog-Cloud Scenario 61; Hamed Shah-Mansouri and Vincent W.S. Wong 3.1 Internet of Things 61 3.2 Fog Computing 63 3.2.1 Overview of Fog Computing 63 3.2.2 Computation Offloading 64 3.2.2.1 Evaluation Criteria 65 3.2.2.2 Literature Review 66 3.3 A Computation Task Offloading Game for Hybrid Fog-Cloud Computing 67 3.3.1 System Model 67 3.3.1.1 Hybrid Fog-Cloud Computing 68 3.3.1.2 Computation Task Models 68 3.3.1.3 Quality of Experience 71 3.3.2 Computation Offloading Game 71 3.3.2.1 Game Formulation 71 3.3.2.2 Algorithm Development 74 3.3.2.3 Price of Anarchy 74 3.3.2.4 Performance Evaluation 75 3.4 Conclusion 80 References 80 4 Pricing Tradeoffs for Data Analytics in Fog–Cloud Scenarios 83; Yichen Ruan, Liang Zheng, Maria Gorlatova, Mung Chiang, and Carlee Joe-Wong 4.1 Introduction: Economics and Fog Computing 83 4.1.1 Fog Application Pricing 85 4.1.2 Incentivizing Fog Resources 86 4.1.3 A Fogonomics Research Agenda 86 4.2 Fog Pricing Today 87 4.2.1 Pricing Network Resources 87 4.2.2 Pricing Computing Resources 89 4.2.3 Pricing and Architecture Trade-offs 89 4.3 Typical Fog Architectures 90 4.3.1 Fog Applications 90 4.3.2 The Cloud-to-Things Continuum 90 4.4 A Case Study: Distributed Data Processing 92 4.4.1 A Temperature Sensor Testbed 92 4.4.2 Latency, Cost, and Risk 95 4.4.3 System Trade-off: Fog or Cloud 98 4.5 Future Research Directions 101 4.6 Conclusion 102 Acknowledgments 102 References 103 5 Quantitative and Qualitative Economic Benefits of Fog 107; Joe Weinman 5.1 Characteristics of Fog Computing Solutions 108 5.2 Strategic Value 109 5.2.1 Information Excellence 110 5.2.2 Solution Leadership 110 5.2.3 Collective Intimacy 110 5.2.4 Accelerated Innovation 111 5.3 Bandwidth, Latency, and Response Time 111 5.3.1 Network Latency 113 5.3.2 Server Latency 114 5.3.3 Balancing Consolidation and Dispersion to Minimize Total Latency 114 5.3.4 Data Traffic Volume 115 5.3.5 Nodes and Interconnections 116 5.4 Capacity, Utilization, Cost, and Resource Allocation 117 5.4.1 Capacity Requirements 117 5.4.2 Capacity Utilization 118 5.4.3 Unit Cost of Delivered Resources 119 5.4.4 Resource Allocation, Sharing, and Scheduling 120 5.5 Information Value and Service Quality 120 5.5.1 Precision and Accuracy 120 5.5.2 Survivability, Availability, and Reliability 122 5.6 Sovereignty, Privacy, Security, Interoperability, and Management 123 5.6.1 Data Sovereignty 123 5.6.2 Privacy and Security 123 5.6.3 Heterogeneity and Interoperability 124 5.6.4 Monitoring, Orchestration, and Management 124 5.7 Trade-Offs 125 5.8 Conclusion 126 References 126 6 Incentive Schemes for User-Provided Fog Infrastructure 129; George Iosifidis, Lin Gao, Jianwei Huang, and Leandros Tassiulas 6.1 Introduction 129 6.2 Technology and Economic Issues in UPIs 132 6.2.1 Overview of UPI models for Network Connectivity 132 6.2.2 Technical Challenges of Resource Allocation 134 6.2.3 Incentive Issues 135 6.3 Incentive Mechanisms for Autonomous Mobile UPIs 137 6.4 Incentive Mechanisms for Provider-assisted Mobile UPIs 140 6.5 Incentive Mechanisms for Large-Scale Systems 143 6.6 Open Challenges in Mobile UPI Incentive Mechanisms 145 6.6.1 Autonomous Mobile UPIs 145 6.6.1.1 Consensus of the Service Provider 145 6.6.1.2 Dynamic Setting 146 6.6.2 Provider-assisted Mobile UPIs 146 6.6.2.1 Modeling the Users 146 6.6.2.2 Incomplete Market Information 147 6.7 Conclusions 147 References 148 7 Fog-Based Service Enablement Architecture 151; Nanxi Chen, Siobhán Clarke, and Shu Chen 7.1 Introduction 151 7.1.1 Objectives and Challenges 152 7.2 Ongoing Effort on FogSEA 153 7.2.1 FogSEA Service Description 156 7.2.2 Semantic Data Dependency Overlay Network 158 7.2.2.1 Creation and Maintenance 159 7.2.2.2 Semantic-Based Service Matchmarking 161 7.3 Early Results 164 7.3.1 Service Composition 165 7.3.1.1 SeDDON Creation in FogSEA 167 7.3.2 Related Work 168 7.3.2.1 Semantic-Based Service Overlays 169 7.3.2.2 Goal-Driven Planning 170 7.3.2.3 Service Discovery 171 7.3.3 Open Issue and Future Work 172 References 174 8 Software-Defined Fog Orchestration for IoT Services 179; Renyu Yang, Zhenyu Wen, David McKee, Tao Lin, Jie Xu, and Peter Garraghan 8.1 Introduction 179 8.2 Scenario and Application 182 8.2.1 Concept Definition 182 8.2.2 Fog-enabled IoT Application 184 8.2.3 Characteristics and Open Challenges 185 8.2.4 Orchestration Requirements 187 8.3 Architecture: A Software-Defined Perspective 188 8.3.1 Solution Overview 188 8.3.2 Software-Defined Architecture 189 8.4 Orchestration 191 8.4.1 Resource Filtering and Assignment 192 8.4.2 Component Selection and Placement 194 8.4.3 Dynamic Orchestration with Runtime QoS 195 8.4.4 Systematic Data-Driven Optimization 196 8.4.5 Machine-Learning for Orchestration 197 8.5 Fog Simulation 198 8.5.1 Overview 198 8.5.2 Simulation for IoT Application in Fog 199 8.5.3 Simulation for Fog Orchestration 201 8.6 Early Experience 202 8.6.1
• Edition: 1st
• Publisher Details: Hoboken, New Jersey : John Wiley & Sons, Inc
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 004.6782; Cloud computing -- Economic aspects
• Languages: English
• ISBNs: 9781119501114; 9781119501107
• Notes: Note: Description based on CIP data; resource not viewed.
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