作者简介 陈南希,中国科学院上海微系统与信息技术研究所副研究员、博士生导师。在都柏林大学取得博士学位,曾在计算机领域科研机构从事助理研究员的工作,具有丰富的科研与开发经验。于2016年11月加入中国科学院上海微系统与信息技术研究所。 长期从事泛在智能、边缘计算、知识图谱等领域研究工作,在边缘计算与物联网、智能服务模型等领域取得多项创新性成果。在IEEE Communications Magazine、IEEE Transactions on Service Computing、IEEE Internet of Things Journal等期刊发表了论文十余篇,申请发明专利十余件,入选市级人才项目扬帆计划等。
目录 Chapter 1 Introduction 1
Chapter 2 Design Concepts for Pervasive Applications 5
2 1 Motivating Scenario:A Smart Public Space 6
2 1 1 Challenges 9
2 1 2 Possible Solutions 11
2 2 Locating A Provider 14
2 2 1 Reactive Discovery 15
2 2 2 Proactive Discovery 16
2 2 3 Planning-based Composition Announcement 18
2 3 Request Routing 21
2 3 1 Controlled Flooding 22
2 3 2 Directory-based 23
2 3 3 Overlay-based 25
2 3 4 Dynamic Controlled Flooding 26
2 4 Composition Planning 28
2 4 1 Open Service Discovery 28
2 4 2 Goal-oriented Planning 30
2 4 3 Decentralized Flexible Backward Planning 31
2 5 Service Binding 32
2 5 1 QoS-based Selection 33
2 5 2 Adaptable Binding 34
2 5 3 On-demand Binding 35
2 5 4 Path Reliability-driven Selection 35
2 5 5 Bind Microservices on-demand 36
2 6 Service Invocation 37
2 6 1 Fragments Distribution 37
2 6 2 Process Migration Approaches 38
2 6 3 Runtime Service Announcement 39
2 7 Fault Tolerance 40
2 7 1 Preventive Adaptation 40
2 7 2 Composition Recovery 42
2 7 3 Local Execution Path Maintenance 43
2 8 Chapter Summary 44
Chapter 3 Microservice Deployment in Edge/Fog Computing Environments 45
3 1 Edge Computing:Pervasive Applications New Enabler 46
3 2 Features in Edge Computing Environments 48
3 2 1 Latency-sensitive 49
3 2 2 Mobility is Everywhere 49
3 2 3 Openness of Network Systems 50
3 2 4 Constantly Changing Environment 50
3 2 5 Limited Power Supply 51
3 3 Fog as a Service Model 51
3 4 Edge/Fog Computing Architecture 54
3 5 Fog Node Overlay Network 56
3 6 Hierarchical Microservices Management 57
3 6 1 Fog Services and Service Composition 57
3 6 2 Proxy Fog Nodes 58
3 6 3 Seamless Service Invocation 59
3 7 Adaptability at Edge 59
3 7 1 Monitoring Environmental Changes 61
3 7 2 Adaptation Analysis Based on Deep Learning 62
3 7 3 Adaptation Planning Based on Reinforcement Learning 63
3 7 4 Strategy Execution and Knowledge Base Utilization 63
3 7 5 Extension of the MAPE-K Framework 64
3 8 Microservice Deployment and Dynamic Redeployment 65
3 9 Examples of Pervasive Applications at Edge 67
3 9 1 Mobile Video 67
3 9 2 Smart Home 68
3 9 3 Computational Offloading 69
3 10 Open Issues to Edge-enabled Pervasive Applications 71
3 10 1 End-to-end Security 71
3 10 2 Distributed Runtime Management 71
3 10 3 Scalability and Reconfigurability 72
3 10 4 Predictive Fault Tolerance 73
3 10 5 Intelligent Edge Computing for 6G 73
3 11 Chapter Summary 74
Chapter 4 Microservices Composition Model 75
4 1 Microservice Model 78
4 2 Dynamic Goal-driven Composition Planning 79
4 2 1 Local Service Planning 84
4 2 2 Complex Service Flows 88
4 3 Heuristic Service Discovery 90
4 4 Execution Fragments Selection and Invocation 93
4 4 1 Microservice Composite Selection and Invocation 94
4 4 2 Service Execution and Guidepost Adaptation 95
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