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
Chapter 2 Design Concepts for Pervasive Applications
2.1 Motivating Scenario: A Smart Public Space
2.1.1 Challenges
2.1.2 Possible Solutions
2.2 Locating A Provider
2.2.1 Reactive Discovery
2.2.2 Proactive Discovery
2.2.3 Planning-based Composition Announcement
2.3 Request Routing
2.3.1 Controlled Flooding
2.3.2 Directory-based
2.3.3 Overlay-based
2.3.4 Dynamic Controlled Flooding
2.4 Composition Planning
2.4.1 Open Service Discovery
2.4.2 Goal-oriented Planning
2.4.3 Decentralized Flexible Backward Planning
2.5 Service Binding
2.5.1 QoS-based Selection
2.5.2 Adaptable Binding
2.5.3 On-demand Binding
2.5.4 Path Reliability-driven Selection
2.5.5 Bind Microservices on-demand
2.6 Service Invocation
2.6.1 Fragments Distribution
2.6.2 Process Migration Approaches
2.6.3 Runtime Service Announcement
2.7 Fault Tolerance
2.7.1 Preventive Adaptation
2.7.2 Composition Recovery
2.7.3 Local Execution Path Maintenance
2.8 Chapter Summary
Chapter 3 Microservice Deployment in Edge/Fog Computing Environments
3.1 Edge Computing: Pervasive Applications New Enabler
3.2 Features in Edge Computing Environments
3.2.1 Latency-sensitive
3.2.2 Mobility is Everywhere
3.2.3 Openness of Network Systems
3.2.4 Constantly Changing Environment
3.2.5 Limited Power Supply
3.3 Fog as a Service Model
3.4 Edge/Fog Computing Architecture
3.5 Fog Node Overlay Network
3.6 Hierarchical Microservices Management
3.6.1 Fog Services and Service Composition
3.6.2 Proxy Fog Nodes
3.6.3 Seamless Service Invocation
3.7 Adaptability at Edge
3.7.1 Monitoring Environmental Changes
3.7.2 Adaptation Analysis Based on Deep Learning
3.7.3 Adaptation Planning Based on Reinforcement Learning
3.7.4 Strategy Execution and Knowledge Base Utilization
3.7.5 Extension of the MAPE-K Framework
3.8 Microservice Deployment and Dynamic Redeployment
3.9 Examples of Pervasive Applications at Edge
3.9.1 Mobile Video
3.9.2 Smart Home
3.9.3 Computational Offloading
3.10 Open Issues to Edge-enabled Pervasive Applications
3.10.1 End-to-end Security
3.10.2 Distributed Runtime Management
3.10.3 Scalability and Reconfigurability
3.10.4 Predictive Fault Tolerance
3.10.5 Intelligent Edge Computing for 6G
3.11 Chapter Summary
Chapter 4 Microservices Composition Model
4.1 Microservice Model
4.2 Dynamic Goal-driven Composition Planning
4.2.1 Local Service Planning
4.2.2 Complex Service Flows
4.3 Heuristic Service Discovery
4.4 Execution Fragments Selection and Invocation
4.4.1 Microservice Composite Selection and Invocation
4.4.2 Service Execution and Guidepost Adaptation
4.5 Discussions
4.5.1 Quantitative Analysis
4.5.2 Service Flows
4.5.3 Privacy and Security
4.5.4 Semantic Matchmaking
4.5.5 High Composition Demand
4.6 Chapter Summary
Chapter 5 Cooperative Microservices Provisioning
5.1 Cooperative Caching and Selfish Caching
5.1.1 Social Behaviours in Caching
5.1.2 Social Selfishness of Service Providers
5.2 Local Optimal Caching Algorithm with Social Selfishness
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