
Edge Computing: A Primer
Description
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Persons
Jie Cao is Assistant Professor (Cybersecurity) in the School of Information Security & Applied Computing at Eastern Michigan University.
Dr. Quan Zhang is a Data Engineer at Salesforce. He was previously a Graduate Research Assistant at Wayne State University.
Content
2 - 1 Introduction [Seite 8]
2.1 - 1.1 What Is Edge Computing [Seite 9]
2.1.1 - 1.1.1 Why Do We Need Edge Computing [Seite 9]
2.1.1.1 - Push from Cloud Services [Seite 9]
2.1.1.2 - Pull from the Internet of Things [Seite 10]
2.1.1.3 - Change from a Data Consumer to Producer [Seite 10]
2.1.2 - 1.1.2 Key Techniques that Enable Edge Computing [Seite 11]
2.1.2.1 - VMs and Containers [Seite 11]
2.1.2.2 - Software Defined Networking (SDN) [Seite 11]
2.1.2.3 - Content Delivery/Distribution Network (CDN) [Seite 11]
2.1.2.4 - Cloudlets and Micro Data Centers (MDC) [Seite 12]
2.1.3 - 1.1.3 Edge Computing Definition [Seite 12]
2.1.4 - 1.1.4 Edge Computing Benefits [Seite 12]
2.1.5 - 1.1.5 Edge Computing Systems [Seite 13]
2.2 - 1.2 Overview of the Book [Seite 14]
2.3 - References [Seite 15]
3 - 2 EdgeOSH: A Home Operating System for Internet of Everything [Seite 17]
3.1 - 2.1 Introduction [Seite 17]
3.2 - 2.2 Related Work [Seite 18]
3.3 - 2.3 EdgeOSH: Overview and Design [Seite 19]
3.3.1 - 2.3.1 Overview [Seite 21]
3.3.2 - 2.3.2 Design [Seite 22]
3.4 - 2.4 Summary [Seite 23]
3.5 - References [Seite 24]
4 - 3 Firework: Data Analytics in Hybrid Cloud-Edge Environment [Seite 25]
4.1 - 3.1 Introduction [Seite 25]
4.2 - 3.2 System Design [Seite 26]
4.2.1 - 3.2.1 Terminologies [Seite 27]
4.2.2 - 3.2.2 Architecture [Seite 28]
4.2.3 - 3.2.3 Programmability [Seite 31]
4.2.4 - 3.2.4 Execution Model Comparison [Seite 36]
4.3 - 3.3 Implementation [Seite 36]
4.4 - 3.4 Discussion [Seite 38]
4.5 - 3.5 Summary [Seite 40]
4.6 - References [Seite 40]
5 - 4 Distributed Collaborative Execution on the Edges and Its Application on AMBER Alert [Seite 42]
5.1 - 4.1 Introduction [Seite 43]
5.2 - 4.2 Motivation [Seite 44]
5.2.1 - 4.2.1 AMBER Alert [Seite 44]
5.2.1.1 - Limitations of Edge Devices [Seite 45]
5.2.1.2 - Control of the Vehicle Tracking Area [Seite 46]
5.2.2 - 4.2.2 Distributed Collaborative Execution on the Edge [Seite 47]
5.3 - 4.3 AMBER Alert Assistant [Seite 47]
5.3.1 - 4.3.1 Application Scenario [Seite 47]
5.3.2 - 4.3.2 Application Design [Seite 48]
5.3.2.1 - Control Center [Seite 48]
5.3.2.2 - Task Receiver [Seite 49]
5.3.2.3 - Data Processor [Seite 49]
5.3.3 - 4.3.3 Implementation Details [Seite 49]
5.3.4 - 4.3.4 Task Scheduling [Seite 51]
5.3.4.1 - Distance-Related Diffusion [Seite 52]
5.3.4.2 - Location-Direction-Related Diffusion [Seite 53]
5.4 - 4.4 Evaluation [Seite 54]
5.4.1 - 4.4.1 Experimental Setup [Seite 54]
5.4.2 - 4.4.2 Collaboration of Local Edge Nodes [Seite 55]
5.4.3 - 4.4.3 Task Scheduling [Seite 58]
5.5 - 4.5 Related Work [Seite 59]
5.6 - 4.6 Summary [Seite 61]
5.7 - References [Seite 61]
6 - 5 Challenges and Opportunities in Edge Computing [Seite 64]
6.1 - 5.1 Programmability [Seite 64]
6.2 - 5.2 Naming [Seite 65]
6.3 - 5.3 Data Abstraction [Seite 66]
6.4 - 5.4 Service Management [Seite 68]
6.5 - 5.5 Privacy and Security [Seite 69]
6.6 - 5.6 Application Distribution [Seite 70]
6.7 - 5.7 Scheduling Strategies [Seite 71]
6.8 - 5.8 Business Model [Seite 72]
6.9 - 5.9 Optimization Metrics [Seite 72]
6.10 - 5.10 Summary [Seite 74]
6.11 - References [Seite 75]
7 - 6 Existing Edge Computing Tools [Seite 76]
7.1 - 6.1 What Is Your Role in Edge Computing? [Seite 76]
7.2 - 6.2 Virtualization [Seite 77]
7.2.1 - 6.2.1 Virtual Machine and Container [Seite 78]
7.2.2 - 6.2.2 Network Virtualization [Seite 81]
7.3 - 6.3 Resource Management [Seite 83]
7.3.1 - 6.3.1 Kubernetes and Docker [Seite 84]
7.4 - 6.4 Developing Platforms for Edge Computing [Seite 86]
7.4.1 - 6.4.1 Edge Analytics [Seite 86]
7.4.2 - 6.4.2 Development Tools and Platforms [Seite 89]
7.5 - 6.5 Summary [Seite 91]
7.6 - References [Seite 91]
8 - 7 Conclusions [Seite 93]
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