Beyond Edge Computing: Swarm Computing and Ad-Hoc Edge Clouds

Disclaimer
Contents
About the Author
1 Introduction
	1.1 Motivation
	1.2 Swarm Computing and Ah-hoc Edge Clouds
	1.3 Book Organisation
	References
Part I Current Status of Computing at the Cloud and Network Edges
	References
	References
2 Setting the Scene: Cloud, Edge, Mobile and Ad-hoc Computing Context
	2.1 Cloud, Edge, Mobile and Ad-hoc Computing Relations
	2.2 Decentralisation of Cloud Computing
	2.3 Edge and Fog Computing Terminology
	References
3 Cloud Computing
	3.1 Introduction to Cloud Computing
	3.2 Basic Definitions, Benefits and Drawbacks
	3.3 Cloud Foundations
		3.3.1 Virtualisation and Containerisation Technologies
		3.3.2 Cloud Native Software Architectures
	3.4 Services in Public Clouds
		3.4.1 Infrastructure-as-a-Service (IaaS)
		3.4.2 Platform-as-a-Service (PaaS)
			3.4.2.1 Programming Frameworks and Tools
			3.4.2.2 Data Management Services
			3.4.2.3 Specialised Programming Approaches
	3.5 Hybrid and Multi-Cloud Management
	References
4 Mobile Cloud Computing
	4.1 Introduction to Mobile Cloud Computing
	4.2 MCC Challenges
		4.2.1 Inherent Mobile Devices Challenges
		4.2.2 Network Connectivity
		4.2.3 Security
		4.2.4 Off-Loading and Application Partitioning
	4.3 MCC Models
	4.4 Analysis of Existing Works in MCC
		4.4.1 Approaches Based on Off-Loading to a Server
			4.4.1.1 MAUI, Making Smartphones Last Longer with Code Offload
			4.4.1.2 Cuckoo, a Computation Offloading Framework for Smartphones
		4.4.2 Approaches Based on Off-Loading to Public/Private Cloud Computing
			4.4.2.1 CloneCloud, Elastic Execution Between Mobile Device and Cloud
			4.4.2.2 ThinkAir
		4.4.3 Approaches Based on Off-Loading to Cloudlets
			4.4.3.1 The Case for VM-Based Cloudlets in Mobile Computing
			4.4.3.2 Gabriel
		4.4.4 Approaches Based on Off-Loading to Other Mobile Devices
			4.4.4.1 Hyrax, Cloud Computing on Mobile Devices Using Map Reduce
			4.4.4.2 A Virtual Cloud Computing Provider for Mobile Devices
		4.4.5 Features Comparison
	References
5 Mobile Ad-hoc Cloud Computing
	5.1 Introduction to Mobile Ad-hoc Cloud Computing (MAC)
	5.2 MAC Challenges
	5.3 MAC Models
	5.4 Analysis of Existing Works in MAC
		5.4.1 Dynamic Mobile Cloud Computing: Ad Hoc and Opportunistic Job Sharing
		5.4.2 MoCCA, A Mobile Cellular Cloud Architecture
		5.4.3 Ad-hoc Cloud as a Service
		5.4.4 MobiCloud
		5.4.5 mClouds
		5.4.6 Aura
	5.5 Features Comparison
	References
6 Edge and Fog Computing
	6.1 Computing Perspective, Edge and Cloud
		6.1.1 Edge Computing Challenges
			6.1.1.1 Edge Management
			6.1.1.2 Edge Interoperability
			6.1.1.3 Cognitive Techniques: AI and ML Applied to Edge Management
			6.1.1.4 Economy
			6.1.1.5 Eco-Efficiency
			6.1.1.6 Security and Privacy
			6.1.1.7 Connectivity and Resilience
		6.1.2 Edge Computing Models
		6.1.3 Existing Works in Research
			6.1.3.1 Fog Computing, a Platform for Internet of Things and Analytics
			6.1.3.2 ANGELS for Distributed Analytics in IoT
			6.1.3.3 Mobile Fog
			6.1.3.4 Nebula
			6.1.3.5 Resource Provisioning for IoT Services in the Fog
		6.1.4 Existing Products in the Market
			6.1.4.1 Azure IoT Edge
			6.1.4.2 AWS Greengrass
		6.1.5 Existing Open-Source Initiatives
			6.1.5.1 K3s
			6.1.5.2 Microk8s
			6.1.5.3 KubeEdge
			6.1.5.4 Starlingx
			6.1.5.5 ONEDge
			6.1.5.6 IoFog
			6.1.5.7 EdgeX Foundry
		6.1.6 Features Comparison
	6.2 Mobile Edge Computing and Networking Perspectives
		6.2.1 ETSI Multi-Access Edge Computing Framework and Reference Architecture
		6.2.2 Existing Products in the Market
			6.2.2.1 Amazon Web Services 5G telco Offerings
			6.2.2.2 Azure 5G telco Offerings
			6.2.2.3 Google Cloud 5G telco Offerings
		6.2.3 Conclusions
	References
7 Additional Technologies for Swarm Development
	7.1 Security Requirements for Computing at the Edge
	7.2 The Role for P2P and Consensus Algorithms
	References
Part II Computing Beyond the Edge: Swarm Computing and Ad-hoc Edge Architectures
	References
	References
8 Computing Beyond Edge: The Swarm Computing Concept
	8.1 Overview
	8.2 Foreseen Evolution Towards Swarm Computing
	8.3 Definition of Ad-hoc Edge Clouds, the Swarm Computing Concept
	8.4 Swarm Computing Characteristics and Principles
		8.4.1 Swarm Characteristics
		8.4.2 Key Principles
			8.4.2.1 Aware
			8.4.2.2 Autonomous
			8.4.2.3 Actionable
	8.5 Ad-hoc Edge Cloud Resources Characteristics
	8.6 Lifecycle of a Swarm
	8.7 Swarm Computing Motivational Use Cases
	References
9 Building Blocks for Ad-hoc Edge Clouds
	9.1 Introduction
	9.2 Ad-hoc Edge Cloud Framework
		9.2.1 Edge Device Context
		9.2.2 Ad-hoc Edge Context
		9.2.3 Ad-hoc Edge Cloud Architecture Flow of Events
		9.2.4 Conclusions
	References
10 Cognitive Resource Management in Ad-hoc Edge Clouds
	10.1 Overview
	10.2  IoT Device Availability Protocol
		10.2.1 Publication
		10.2.2 Registration
		10.2.3 Select
		10.2.4 Use
		10.2.5 Release
		10.2.6 Un-register
	10.3 Ad-hoc Edge Cluster Instantiation and Management
		10.3.1 Ad-hoc Edge Cluster Instantiation
		10.3.2 Ad-hoc Edge Cluster Management
			10.3.2.1 Cluster Operation
			10.3.2.2 Node Addition
			10.3.2.3 Node Failure
	10.4 Evaluation
		10.4.1 Lab Evaluation
			10.4.1.1 Scalability Experimentation
			10.4.1.2 Availability/Churn Rates Experimentation
		10.4.2 Large Scale Evaluation in AWS EC2
			10.4.2.1 Scalability Experimentation
			10.4.2.2 Large Scale Evaluation via AWS A1
	10.5 Conclusions
	References
11 Service Placement and Management
	11.1 Overview
		11.1.1 Admission Control in Service Lifecycle of Ad-hoc Edge Infrastructure
	11.2 Ad-hoc Edge Service Model
	11.3 Admission Control Mechanism Formulation
		11.3.1 Resource Availability Prediction
	11.4 Evaluation
		11.4.1 Node Quality
		11.4.2 Service Quality
	11.5 Related Works
	11.6 Conclusions
	References
Part III Looking Ahead, Next Steps for Ad-hoc Edge Clouds and Swarm Computing Realization
12 Next Steps for Ad-hoc Edge Cloud and Swarm Computing Realization
	12.1 Edge Computing Research Areas
		12.1.1 Heterogeneity Exploitation and New Hardware Architectures: Neuromorphic Edge Computing
		12.1.2 Energy Efficiency Optimisation
		12.1.3 Multi-Level Edge
		12.1.4 Edge Intelligence
		12.1.5 Data Management
		12.1.6 Edge Management
		12.1.7 Computing Continuum Exploration
	12.2 Swarm Computing Research Areas
		12.2.1 Swarm Management Techniques
		12.2.2 Resource Discovery
		12.2.3 Self-management and Autonomic Systems
		12.2.4 Bio Inspired Optimisation Techniques
	References