Edge/Fog Computing Paradigm: The Concept, Platforms and Applications.
- 1st Edition, Volume 127 - April 21, 2022
- Imprint: Academic Press
- 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
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Request a sales quoteAdvances 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.
- Contains novel subject matter that is relevant to computer science
- Includes the expertise of contributing authors
- Presents an easy to comprehend writing style
Researchers in high performance computer areas, hardware manufacturers, educational programs in physics and scientific computation and in computer science
- 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
- Edition: 1
- Volume: 127
- Published: April 21, 2022
- No. of pages (Hardback): 560
- No. of pages (eBook): 560
- Imprint: Academic Press
- Language: English
- Hardback ISBN: 9780128245064
- eBook ISBN: 9780128245071
PR
Pethuru Raj
Pethuru Raj PhD works as 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, IndiaKS
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, IndiaCS
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, IndiaRead Edge/Fog Computing Paradigm: The Concept, Platforms and Applications. on ScienceDirect