Edge/Fog Computing Paradigm: The Concept, Platforms and Applications.

1st Edition, Volume 127 - April 21, 2022
Editors: Pethuru Raj, Kavita Saini, Chellammal Surianarayanan
Language: English
Hardback ISBN:
9 7 8 - 0 - 1 2 - 8 2 4 5 0 6 - 4
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 2 4 5 0 7 - 1

Advances in Computers, Volume 127 presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on Edge AI,… Read more

Edge/Fog Computing Paradigm: The Concept, Platforms and Applications.

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Advances in Computers, Volume 127 presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on Edge AI, Edge Computing, Edge Analytics, Edge Data Analytics, Edge Native Applications, Edge Platforms, Edge Computing, IoT, Internet of Things, etc.

Cover image
Title page
Table of Contents
Copyright
Contributors
Preface
Chapter One: Exploring the edge AI space_ Industry use cases
Abstract
1: The proliferation of IoT devices and sensors
2: Activating on-device intelligence
3: The artificial intelligence (AI) processing at the edge
4: Machine learning (ML) at the edge
5: Deep learning at the edge
6: Digging into the paradigm of edge AI
7: Edge AI for next-generation retail experiences
8: Edge AI for smarter cities
9: Edge AI for telecommunication
10: Conclusion
Further reading
Chapter Two: Edge computing: Types and attributes
Abstract
1: Introduction
2: Internet of Things (IoT) edge
3: On-premises edge
4: Wireless Access Edge
5: Network edge
6: Challenges in edge computing
7: Multi-Access Edge Computing
References
Chapter Three: Industry initiatives across edge computing
Abstract
1: Linux Foundation Edge
2: Linux Foundation for Networking
3: O-RAN alliance
4: Open Network Foundation
5: 3GPP
6: Small Cell Forum
7: Broadband Forum
8: 5G Alliance for connected industry and automation (5G-ACIA)
9: 5G Automotive Association (5GAA)
10: Automotive Edge Computing Consortium (AECC)
11: Telecom Infra Project
12: IEEE International Network Generations Roadmap Edge Services Platform (ESP)
13: KubeEdge
14: StarlingX
15: Open Edge Computing Initiative
16: Smart Edge Open
17: Edge Multi Cluster Orchestrator (EMCO)
18: Global Systems for Mobile Association (GSMA)
References
Chapter Four: IoT-edge analytics for BACON-assisted multivariate health data anomalies
Abstract
1: Introduction
2: Related works
3: System design
4: Results
5: Conclusion
References
Chapter Five: The edge AI paradigm: Technologies, platforms and use cases
Abstract
1: Introduction
2: Delineating the two paradigms
3: Tending toward the digital era
4: The key connectivity technologies
5: The 5G use cases and benefits
6: About edge computing
7: Edge computing architecture
8: Edge cloud infrastructures
9: Edge analytics
10: The key benefits of edge computing
11: Tending toward edge AI
12: Artificial intelligence (AI) chips for edge devices
13: The noteworthy trends toward edge AI
14: Why edge processing?
15: Edge-based AI solutions: The advantages
16: Applications that can be performed on edge devices
17: Edge AI use cases
18: Conclusion
Chapter Six: Microservices architecture for edge computing environments
Abstract
1: Introduction
2: Need for edge and fog computing
3: Nature and requirements in edge and fog computing environment
4: Why microservices architecture for edge/fog computing applications?
5: How the unique features of MSA fits as a natural choice for edge and fog layers?
6: Overview about elements of microservices
7: MSA for edge/fog computing
8: Challenges
9: Conclusion
References
Chapter Seven: Edge data analytics technologies and tools
Abstract
1: Introduction to edge data analytics and benefits
2: Edge data analytics versus server-based data analytics
3: Architecture and methodology of edge data analytics
4: Edge data analytics technologies and solutions
5: Working principles and feature comparisons
6: Some of the other use cases of edge analytics [19,20]
References
Chapter Eight: Edge platforms, frameworks and applications
Abstract
1: Introduction to cloud computing
2: Cloud computing to edge computing
3: Edge computing: A brief overview
4: Essential of edge computing
5: Advantages of edge computing
6: Significance of cloudlets
7: Conclusion
References
Chapter Nine: Edge computing challenges and concerns
Abstract
1: Introduction
2: Cloud, fog and edge computing
3: Implications and challenges in adopting edge computing
4: Concerns with edge computing
5: Security and privacy attacks on edge computing enabled devices
6: Countermeasures to security and privacy attacks in edge infrastructure
7: Future of edge computing
8: Conclusion
References
Further reading
Chapter Ten: A smart framework through the Internet of Things and machine learning for precision agriculture
Abstract
1: Introduction
2: Existing infrastructure in agriculture
3: IoT ecosystem—A complete view
4: Agricultural monitoring system based on sensors
5: Difficulties in sensor-based agribusiness observing frameworks
6: Factors affecting climatic changes in savvy agribusiness
7: AI in agriculture—An introduction
8: Machine learning techniques for smart agriculture
9: Artificial neural network (ANN)
10: Automation and wireless system networks in agriculture
11: Hardware components in the smart agriculture system
12: Use cases
13: Conclusion
References
Chapter Eleven: 5G Communication for edge computing
Abstract
1: Introduction
2: Architectures of edge computing
3: 5G and edge computing
4: 5G and edge computing use cases
5: Challenges during the deployment of edge computing in 5G
6: Conclusion
References
Chapter Twelve: The future of edge computing
Abstract
1: Introduction
2: Emergence of edge computing
3: Drawbacks of out-of-date cloud computing
4: Significance of edge computing
5: Edge computing technologies
6: Possible advancements in digitization using edge computing
7: Opportunities for edge in future
8: Conclusion
References
Chapter Thirteen: Edge computing security: Layered classification of attacks and possible countermeasures
Abstract
1: Introduction
2: Four layer architecture of edge computing
3: Security attacks in edge computing: Layered classification and analysis
4: Edge based existing solutions for the security issues present in real world IoT applications
5: Discussion
6: Conclusion and future works
References
Chapter Fourteen: Blockchain technology for IoT edge devices and data security
Abstract
1: Introduction
2: IoT layered architecture
3: IoT security threats and attacks
4: IoT—Edge computing
5: Requirements for integration of blockchain and edge computing
6: Integration of blockchain and edge computing
7: IoT framework: Secure edge computing with blockchain technology
8: Factors to be addressed in secure edge computing
9: Advantages—Integration of blockchain and edge computing
10: Use cases—Blockchain with edge computing
11: Further challenges and recommendations
12: Conclusion
References
Chapter Fifteen: EDGE/FOG computing paradigm: Concept, platforms and toolchains
Abstract
1: Introduction
2: Machine learning (ML) in FC
3: Classes of service for fog applications
4: Clusters for lightweight edge clouds
5: IoT Application with fog real time application
6: Safeguarding data consistency at the edge
7: Cloud-fog-edge-IoT collaborative framework
8: Edge computing with machine learning
9: Security challenges in fog computing
10: Conclusion
Reference
Chapter Sixteen: Artificial intelligence in edge devices
Abstract
1: Introduction
2: Primer on artificial intelligence
3: Edge intelligence
4: Edge intelligence model training
5: Edge intelligence model interface
6: Future research directions
7: Conclusions
References
Further reading
Chapter Seventeen: 5G—Communication in HealthCare applications
Abstract
1: Introduction
2: 5G—IOT for E-healthcare
3: 5G—Industrial Internet of Thongs (IIoT)
4: 5G—Network requirements for healthcare
5: 5G—Virtual HealthCare
6: TeleHealth vs. virtual health
7: 5G—Remote HealthCare monitoring
8: 5G—Remote surgery
9: 5G—Futures and robotics in healthcare
10: 5G—Impact on HealthCare
11: Conclusion
References
Chapter Eighteen: The integration of blockchain and IoT edge devices for smart agriculture: Challenges and use cases
Abstract
1: Introduction
2: Blockchain technology: An overview
3: Working of blockchain
4: IoT: An overview
5: Working of IoT
6: Edge computing: An overview
7: A proposed model for smart agriculture using blockchain and IoT
8: Advantages of blockchain, edge computing and IoT based agriculture
9: Summary of the research for applying blockchain and IoT in agriculture (Table 2)
10: Challenges and open issues
11: Conclusion
References

Pethuru Raj

Pethuru Raj PhD has been working as a chief architect and vice president of site reliability engineering (SRE) division of Reliance Jio Infocomm. Ltd. Bangalore. Previously he worked as a cloud infrastructure architect in the IBM Global Cloud Center of Excellence (CoE), Bangalore. He worked as a TOGAF-certified enterprise architecture (EA) consultant in Wipro Consulting Services (WCS) Division and as a lead architect in the corporate research (CR) division of Robert Bosch, India. He has gained more than 18 years of IT industry experience. He finished the CSIR-sponsored PhD degree in Anna University, Chennai and continued the UGC-sponsored postdoctoral research in the department of Computer Science and Automation, Indian Institute of Science, Bangalore. Thereafter, he was granted a couple of international research fellowships (JSPS and JST) to work as a research scientist for 3.5 years in two leading Japanese universities. He has authored and edited 18 books thus far and he focuses on some of the emerging technologies such as Containerized Clouds; Big, Fast, and Streaming Data Analytics; Microservices architecture (MSA); Machine and Deep Learning Algorithms; Blockchain Technology; The Internet of Things; and Edge Computing. He has published more than 30 research papers in peer-reviewed journals such as IEEE, ACM, Springer-Verlag, Inderscience, etc.

Affiliations and expertise

Reliance Jio Platforms Ltd.. (RJIL), Bangalore, India

Kavita Saini

Prof. Kavita Saini is an Experienced Program Chair with a demonstrated history of working in the higher education industry. She is skilled in Blockchain, Data Structure , Database management System, E-Learning,C and C++, and Editing. She is a strong engineering professional with a Doctor of Philosophy - PhD focused in Computer Science from Banasthali Vidyapeeth .

Affiliations and expertise

Associate Professor, Galgotias University, Greater Noida, Gautam buddh Nagar, Uttar Pradesh, India

Chellammal Surianarayanan

Prof. Chellammal Surianarayanan is currently serving as Assistant Professor in the Department of Computer Science, Bharathidasan University Constituent Arts & Science. She is a competent professional having 21 years of total experience, with 12 years of experience in Research & Development and 9 years of experience as academician. She has served for India Comnet International Chennai (Tellabs USA Client) and at Indira Gandhi Centre for Atomic Research (IGCAR), Department of Atomic Energy Government of India as Scientific Officer/E. With the work experience, she has gained expertise in development of specific need based embedded systems, semantic web services, data minging, big data.

Affiliations and expertise

Assistant Professor in Computer Science, Bharathidasan University Constituent Arts and Science College, India