Artificial Intelligence For Edge Computing

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Edge AI

Xiaofei Wang,Yiwen Han,Victor C. M. Leung,Dusit Niyato,Xueqiang Yan,Xu Chen
Edge AI Book PDF

Author : Xiaofei Wang,Yiwen Han,Victor C. M. Leung,Dusit Niyato,Xueqiang Yan,Xu Chen
Publisher : Springer Nature
Page : 156 pages
File Size : 41,6 Mb
Release : 2020-08-31
Category : Computers
ISBN : 9789811561863

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Edge AI by Xiaofei Wang,Yiwen Han,Victor C. M. Leung,Dusit Niyato,Xueqiang Yan,Xu Chen Pdf

As an important enabler for changing people’s lives, advances in artificial intelligence (AI)-based applications and services are on the rise, despite being hindered by efficiency and latency issues. By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial. To do so, it introduces and discusses: 1) edge intelligence and intelligent edge; and 2) their implementation methods and enabling technologies, namely AI training and inference in the customized edge computing framework. Gathering essential information previously scattered across the communication, networking, and AI areas, the book can help readers to understand the connections between key enabling technologies, e.g. a) AI applications in edge; b) AI inference in edge; c) AI training for edge; d) edge computing for AI; and e) using AI to optimize edge. After identifying these five aspects, which are essential for the fusion of edge computing and AI, it discusses current challenges and outlines future trends in achieving more pervasive and fine-grained intelligence with the aid of edge computing.

Artificial Intelligence for Cloud and Edge Computing

Sanjay Misra,Amit Kumar Tyagi,Vincenzo Piuri,Lalit Garg
Artificial Intelligence for Cloud and Edge Computing Book PDF

Author : Sanjay Misra,Amit Kumar Tyagi,Vincenzo Piuri,Lalit Garg
Publisher : Springer Nature
Page : 358 pages
File Size : 45,9 Mb
Release : 2022-01-13
Category : Computers
ISBN : 9783030808211

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Artificial Intelligence for Cloud and Edge Computing by Sanjay Misra,Amit Kumar Tyagi,Vincenzo Piuri,Lalit Garg Pdf

This book discusses the future possibilities of AI with cloud computing and edge computing. The main goal of this book is to conduct analyses, implementation and discussion of many tools (of artificial intelligence, machine learning and deep learning and cloud computing, fog computing, and edge computing including concepts of cyber security) for understanding integration of these technologies. With this book, readers can quickly get an overview of these emerging topics and get many ideas of the future of AI with cloud, edge, and in many other areas. Topics include machine and deep learning techniques for Internet of Things based cloud systems; security, privacy and trust issues in AI based cloud and IoT based cloud systems; AI for smart data storage in cloud-based IoT; blockchain based solutions for AI based cloud and IoT based cloud systems.This book is relevent to researchers, academics, students, and professionals.

Artificial Intelligence for Edge Computing

Mudhakar Srivatsa,Tarek Abdelzaher,Ting He
Artificial Intelligence for Edge Computing Book PDF

Author : Mudhakar Srivatsa,Tarek Abdelzaher,Ting He
Publisher : Springer Nature
Page : 373 pages
File Size : 52,9 Mb
Release : 2024-01-10
Category : Technology & Engineering
ISBN : 9783031407871

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Artificial Intelligence for Edge Computing by Mudhakar Srivatsa,Tarek Abdelzaher,Ting He Pdf

It is undeniable that the recent revival of artificial intelligence (AI) has significantly changed the landscape of science in many application domains, ranging from health to defense and from conversational interfaces to autonomous cars. With terms such as “Google Home”, “Alexa”, and “ChatGPT” becoming household names, the pervasive societal impact of AI is clear. Advances in AI promise a revolution in our interaction with the physical world, a domain where computational intelligence has always been envisioned as a transformative force toward a better tomorrow. Depending on the application family, this domain is often referred to as Ubiquitous Computing, Cyber-Physical Computing, or the Internet of Things. The underlying vision is driven by the proliferation of cheap embedded computing hardware that can be integrated easily into myriads of everyday devices from consumer electronics, such as personal wearables and smart household appliances, to city infrastructure and industrial process control systems. One common trait across these applications is that the data that the application operates on come directly (typically via sensors) from the physical world. Thus, from the perspective of communication network infrastructure, the data originate at the network edge. From a performance standpoint, there is an argument to be made that such data should be processed at the point of collection. Hence, a need arises for Edge AI -- a genre of AI where the inference, and sometimes even the training, are performed at the point of need, meaning at the edge where the data originate. The book is broken down into three parts: core problems, distributed problems, and other cross-cutting issues. It explores the challenges arising in Edge AI contexts. Some of these challenges (such as neural network model reduction to fit resource-constrained hardware) are unique to the edge environment. They need a novel category of solutions that do not parallel more typical concerns in mainstream AI. Others are adaptations of mainstream AI challenges to the edge space. An example is overcoming the cost of data labeling. The labeling problem is pervasive, but its solution in the IoT application context is different from other contexts. This book is not a survey of the state of the art. With thousands of publications appearing in AI every year, such a survey is doomed to be incomplete on arrival. It is also not a comprehensive coverage of all the problems in the space of Edge AI. Different applications pose different challenges, and a more comprehensive coverage should be more application specific. Instead, this book covers some of the more endemic challenges across the range of IoT/CPS applications. To offer coverage in some depth, we opt to cover mainly one or a few representative solutions for each of these endemic challenges in sufficient detail, rather that broadly touching on all relevant prior work. The underlying philosophy is one of illustrating by example. The solutions are curated to offer insight into a way of thinking that characterizes Edge AI research and distinguishes its solutions from their more mainstream counterparts.

Machine Learning for Edge Computing

Amitoj Singh,Vinay Kukreja,Taghi Javdani Gandomani
Machine Learning for Edge Computing Book PDF

Author : Amitoj Singh,Vinay Kukreja,Taghi Javdani Gandomani
Publisher : CRC Press
Page : 200 pages
File Size : 52,6 Mb
Release : 2022-07-29
Category : Computers
ISBN : 9781000609233

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Machine Learning for Edge Computing by Amitoj Singh,Vinay Kukreja,Taghi Javdani Gandomani Pdf

This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it discusses how to build AI models, i.e., model training and inference, on edge. This book provides insights into this new inter-disciplinary field of edge computing from a broader vision and perspective. The authors discuss machine learning algorithms for edge computing as well as the future needs and potential of the technology. The authors also explain the core concepts, frameworks, patterns, and research roadmap, which offer the necessary background for potential future research programs in edge intelligence. The target audience of this book includes academics, research scholars, industrial experts, scientists, and postgraduate students who are working in the field of Internet of Things (IoT) or edge computing and would like to add machine learning to enhance the capabilities of their work. This book explores the following topics: Edge computing, hardware for edge computing AI, and edge virtualization techniques Edge intelligence and deep learning applications, training, and optimization Machine learning algorithms used for edge computing Reviews AI on IoT Discusses future edge computing needs Amitoj Singh is an Associate Professor at the School of Sciences of Emerging Technologies, Jagat Guru Nanak Dev Punjab State Open University, Punjab, India. Vinay Kukreja is a Professor at the Chitkara Institute of Engineering and Technology, Chitkara University, Punjab, India. Taghi Javdani Gandomani is an Assistant Professor at Shahrekord University, Shahrekord, Iran.

Artificial Intelligence and Machine Learning for EDGE Computing

Rajiv Pandey,Sunil Kumar Khatri,Neeraj Kumar Singh,Parul Verma
Artificial Intelligence and Machine Learning for EDGE Computing Book PDF

Author : Rajiv Pandey,Sunil Kumar Khatri,Neeraj Kumar Singh,Parul Verma
Publisher : Academic Press
Page : 516 pages
File Size : 47,9 Mb
Release : 2022-04-26
Category : Science
ISBN : 9780128240557

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Artificial Intelligence and Machine Learning for EDGE Computing by Rajiv Pandey,Sunil Kumar Khatri,Neeraj Kumar Singh,Parul Verma Pdf

Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering. Provides a reference handbook on the evolution of distributed systems, including Cloud, Fog and Edge Computing Integrates the various Artificial Intelligence and Machine Learning techniques for effective predictions at Edge rather than Cloud or remote Data Centers Provides insight into the features and constraints in Edge Computing and storage, including hardware constraints and the technological/architectural developments that shall overcome those constraints

Edge Intelligence in the Making

Sen Lin,Zhi Zhou,Zhaofeng Zhang,Xu Chen,Junshan Zhang
Edge Intelligence in the Making Book PDF

Author : Sen Lin,Zhi Zhou,Zhaofeng Zhang,Xu Chen,Junshan Zhang
Publisher : Springer Nature
Page : 17 pages
File Size : 51,7 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031023804

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Edge Intelligence in the Making by Sen Lin,Zhi Zhou,Zhaofeng Zhang,Xu Chen,Junshan Zhang Pdf

With the explosive growth of mobile computing and Internet of Things (IoT) applications, as exemplified by AR/VR, smart city, and video/audio surveillance, billions of mobile and IoT devices are being connected to the Internet, generating zillions of bytes of data at the network edge. Driven by this trend, there is an urgent need to push the frontiers of artificial intelligence (AI) to the network edge to fully unleash the potential of IoT big data. Indeed, the marriage of edge computing and AI has resulted in innovative solutions, namely edge intelligence or edge AI. Nevertheless, research and practice on this emerging inter-disciplinary field is still in its infancy stage. To facilitate the dissemination of the recent advances in edge intelligence in both academia and industry, this book conducts a comprehensive and detailed survey of the recent research efforts and also showcases the authors' own research progress on edge intelligence. Specifically, the book first reviews the background and present motivation for AI running at the network edge. Next, it provides an overview of the overarching architectures, frameworks, and emerging key technologies for deep learning models toward training/inference at the network edge. To illustrate the research problems for edge intelligence, the book also showcases four of the authors' own research projects on edge intelligence, ranging from rigorous theoretical analysis to studies based on realistic implementation. Finally, it discusses the applications, marketplace, and future research opportunities of edge intelligence. This emerging interdisciplinary field offers many open problems and yet also tremendous opportunities, and this book only touches the tip of iceberg. Hopefully, this book will elicit escalating attention, stimulate fruitful discussions, and open new directions on edge intelligence.

Machine Learning for Edge Computing

Amitoj Singh,Vinay Kukreja,Taghi Javdani Gandomani
Machine Learning for Edge Computing Book PDF

Author : Amitoj Singh,Vinay Kukreja,Taghi Javdani Gandomani
Publisher : CRC Press
Page : 200 pages
File Size : 51,5 Mb
Release : 2022-07-29
Category : Computers
ISBN : 9781000609233

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Machine Learning for Edge Computing by Amitoj Singh,Vinay Kukreja,Taghi Javdani Gandomani Pdf

This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it discusses how to build AI models, i.e., model training and inference, on edge. This book provides insights into this new inter-disciplinary field of edge computing from a broader vision and perspective. The authors discuss machine learning algorithms for edge computing as well as the future needs and potential of the technology. The authors also explain the core concepts, frameworks, patterns, and research roadmap, which offer the necessary background for potential future research programs in edge intelligence. The target audience of this book includes academics, research scholars, industrial experts, scientists, and postgraduate students who are working in the field of Internet of Things (IoT) or edge computing and would like to add machine learning to enhance the capabilities of their work. This book explores the following topics: Edge computing, hardware for edge computing AI, and edge virtualization techniques Edge intelligence and deep learning applications, training, and optimization Machine learning algorithms used for edge computing Reviews AI on IoT Discusses future edge computing needs Amitoj Singh is an Associate Professor at the School of Sciences of Emerging Technologies, Jagat Guru Nanak Dev Punjab State Open University, Punjab, India. Vinay Kukreja is a Professor at the Chitkara Institute of Engineering and Technology, Chitkara University, Punjab, India. Taghi Javdani Gandomani is an Assistant Professor at Shahrekord University, Shahrekord, Iran.

Soft Computing Techniques in Engineering, Health, Mathematical and Social Sciences

Pradip Debnath,S. A. Mohiuddine
Soft Computing Techniques in Engineering Health Mathematical and Social Sciences Book PDF

Author : Pradip Debnath,S. A. Mohiuddine
Publisher : CRC Press
Page : 232 pages
File Size : 47,8 Mb
Release : 2021-07-15
Category : Computers
ISBN : 9781000409819

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Soft Computing Techniques in Engineering, Health, Mathematical and Social Sciences by Pradip Debnath,S. A. Mohiuddine Pdf

Soft computing techniques are no longer limited to the arena of computer science. The discipline has an exponentially growing demand in other branches of science and engineering and even into health and social science. This book contains theory and applications of soft computing in engineering, health, and social and applied sciences. Different soft computing techniques such as artificial neural networks, fuzzy systems, evolutionary algorithms and hybrid systems are discussed. It also contains important chapters in machine learning and clustering. This book presents a survey of the existing knowledge and also the current state of art development through original new contributions from the researchers. This book may be used as a one-stop reference book for a broad range of readers worldwide interested in soft computing. In each chapter, the preliminaries have been presented first and then the advanced discussion takes place. Learners and researchers from a wide variety of backgrounds will find several useful tools and techniques to develop their soft computing skills. This book is meant for graduate students, faculty and researchers willing to expand their knowledge in any branch of soft computing. The readers of this book will require minimum prerequisites of undergraduate studies in computation and mathematics.

Applied Edge AI

Pethuru Raj,G. Nagarajan,R.I. Minu
Applied Edge AI Book PDF

Author : Pethuru Raj,G. Nagarajan,R.I. Minu
Publisher : CRC Press
Page : 334 pages
File Size : 51,9 Mb
Release : 2022-04-06
Category : Computers
ISBN : 9781000552690

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Applied Edge AI by Pethuru Raj,G. Nagarajan,R.I. Minu Pdf

The strategically sound combination of edge computing and artificial intelligence (AI) results in a series of distinct innovations and disruptions enabling worldwide enterprises to visualize and realize next-generation software products, solutions and services. Businesses, individuals, and innovators are all set to embrace and experience the sophisticated capabilities of Edge AI. With the faster maturity and stability of Edge AI technologies and tools, the world is destined to have a dazzling array of edge-native, people-centric, event-driven, real-time, service-oriented, process-aware, and insights-filled services. Further on, business workloads and IT services will become competent and cognitive with state-of-the-art Edge AI infrastructure modules, AI algorithms and models, enabling frameworks, integrated platforms, accelerators, high-performance processors, etc. The Edge AI paradigm will help enterprises evolve into real-time and intelligent digital organizations. Applied Edge AI: Concepts, Platforms, and Industry Use Cases focuses on the technologies, processes, systems, and applications that are driving this evolution. It examines the implementation technologies; the products, processes, platforms, patterns, and practices; and use cases. AI-enabled chips are exclusively used in edge devices to accelerate intelligent processing at the edge. This book examines AI toolkits and platforms for facilitating edge intelligence. It also covers chips, algorithms, and tools to implement Edge AI, as well as use cases. FEATURES The opportunities and benefits of intelligent edge computing Edge architecture and infrastructure AI-enhanced analytics in an edge environment Encryption for securing information An Edge AI system programmed with Tiny Machine learning algorithms for decision making An improved edge paradigm for addressing the big data movement in IoT implementations by integrating AI and caching to the edge Ambient intelligence in healthcare services and in development of consumer electronic systems Smart manufacturing of unmanned aerial vehicles (UAVs) AI, edge computing, and blockchain in systems for environmental protection Case studies presenting the potential of leveraging AI in 5G wireless communication

Embedded Artificial Intelligence

Ovidiu Vermesan,Mario Diaz Nava,Björn Debaillie
Embedded Artificial Intelligence Book PDF

Author : Ovidiu Vermesan,Mario Diaz Nava,Björn Debaillie
Publisher : CRC Press
Page : 143 pages
File Size : 51,9 Mb
Release : 2023-05-05
Category : Computers
ISBN : 9781000881912

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Embedded Artificial Intelligence by Ovidiu Vermesan,Mario Diaz Nava,Björn Debaillie Pdf

Recent technological developments in sensors, edge computing, connectivity, and artificial intelligence (AI) technologies have accelerated the integration of data analysis based on embedded AI capabilities into resource-constrained, energy-efficient hardware devices for processing information at the network edge. Embedded AI combines embedded machine learning (ML) and deep learning (DL) based on neural networks (NN) architectures such as convolutional NN (CNN), or spiking neural network (SNN) and algorithms on edge devices and implements edge computing capabilities that enable data processing and analysis without optimised connectivity and integration, allowing users to access data from various sources. Embedded AI efficiently implements edge computing and AI processes on resource-constrained devices to mitigate downtime and service latency, and it successfully merges AI processes as a pivotal component in edge computing and embedded system devices. Embedded AI also enables users to reduce costs, communication, and processing time by assembling data and by supporting user requirements without the need for continuous interaction with physical locations. This book provides an overview of the latest research results and activities in industrial embedded AI technologies and applications, based on close cooperation between three large-scale ECSEL JU projects, AI4DI, ANDANTE, and TEMPO. The book’s content targets researchers, designers, developers, academics, post-graduate students and practitioners seeking recent research on embedded AI. It combines the latest developments in embedded AI, addressing methodologies, tools, and techniques to offer insight into technological trends and their use across different industries.

Edge Computing

K. Anitha Kumari,G. Sudha Sadasivam,D. Dharani,M. Niranjanamurthy
Edge Computing Book PDF

Author : K. Anitha Kumari,G. Sudha Sadasivam,D. Dharani,M. Niranjanamurthy
Publisher : CRC Press
Page : 180 pages
File Size : 43,7 Mb
Release : 2021-11-22
Category : Computers
ISBN : 9781000483598

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Edge Computing by K. Anitha Kumari,G. Sudha Sadasivam,D. Dharani,M. Niranjanamurthy Pdf

This reference text presents the state-of-the-art in edge computing, its primitives, devices and simulators, applications, and healthcare-based case studies. The text provides integration of blockchain with edge computing systems and integration of edge with Internet of Things (IoT) and cloud computing. It will facilitate readers to setup edge-based environment and work with edge analytics. It covers important topics, including cluster computing, fog computing, networking architecture, edge computing simulators, edge analytics, privacy-preserving schemes, edge computing with blockchain, autonomous vehicles, and cross-domain authentication. Aimed at senior undergraduate, graduate students and professionals in the fields of electrical engineering, electronics engineering, computer science, and information technology, this text: Discusses edge data storage security with case studies and blockchain integration with the edge computing system Covers theoretical methods with the help of applications, use cases, case studies, and examples Provides healthcare real-time case studies elaborated by utilizing the virtues of homomorphic encryption Discusses real-time interfaces, devices, and simulators in detail

Edge Computational Intelligence for AI-Enabled IoT Systems

Shrikaant Kulkarni,Jaiprakash Dwivedi,Dinda Pramanta,Yuichiro Tanaka
Edge Computational Intelligence for AI Enabled IoT Systems Book PDF

Author : Shrikaant Kulkarni,Jaiprakash Dwivedi,Dinda Pramanta,Yuichiro Tanaka
Publisher : CRC Press
Page : 347 pages
File Size : 46,9 Mb
Release : 2024-02-26
Category : Computers
ISBN : 9781003825128

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Edge Computational Intelligence for AI-Enabled IoT Systems by Shrikaant Kulkarni,Jaiprakash Dwivedi,Dinda Pramanta,Yuichiro Tanaka Pdf

Edge computational intelligence is an interface between edge computing and artificial intelligence (AI) technologies. This interfacing represents a paradigm shift in the world of work by enabling a broad application areas and customer-friendly solutions. Edge computational intelligence technologies are just in their infancy. Edge Computational Intelligence for AI-Enabled IoT Systems looks at the trends and advances in edge computing and edge AI, the services rendered by them, related security and privacy issues, training algorithms, architectures, and sustainable AI-enabled IoT systems. Together, these technologies benefit from ultra-low latency, faster response times, lower bandwidth costs and resilience from network failure, and the book explains the advantages of systems and applications using intelligent IoT devices that are at the edge of a network and close to users. It explains how to make most of edge and cloud computing as complementary technologies or used in isolation for extensive and widespread applications. The advancement in IoT devices, networking facilities, parallel computation and 5G, and robust infrastructure for generalized machine learning have made it possible to employ edge computational intelligence in diverse areas and in diverse ways. The book begins with chapters that cover Edge AI services on offer as compared to conventional systems. These are followed by chapters that discuss security and privacy issues encountered during the implementation and execution of edge AI and computing services The book concludes with chapters looking at applications spread across different areas of edge AI and edge computing and also at the role of computational intelligence in AI-driven IoT systems.

Edge Intelligence

Javid Taheri,Schahram Dustdar,Albert Zomaya,Shuiguang Deng
Edge Intelligence Book PDF

Author : Javid Taheri,Schahram Dustdar,Albert Zomaya,Shuiguang Deng
Publisher : Springer
Page : 0 pages
File Size : 46,6 Mb
Release : 2023-05-14
Category : Computers
ISBN : 3031221540

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Edge Intelligence by Javid Taheri,Schahram Dustdar,Albert Zomaya,Shuiguang Deng Pdf

This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. It starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from Edge Computing platforms. The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container technologies and how they are used to implement programmable edge computing platforms. Chapter 3 introduces ways to employ AI/ML approaches to optimize service lifecycles at the edge. Chapter 4 goes deeper in the use of AI/ML and introduces ways to optimize spreading computational tasks along edge computing platforms. Chapter 5 introduces AI/ML pipelines to efficiently process generated data on the edge. Chapter 6 introduces ways to implement AI/ML systems on the edge and ways to deal with their training and inferencing procedures considering the limited resources available at the edge-nodes. Chapter 7 motivates the creation of a new orchestrator independent object model to descriptive objects (nodes, applications, etc.) and requirements (SLAs) for underlying edge platforms. To provide hands-on experience to students and step-by-step improve their technical capabilities, seven sets of Tutorials-and-Labs (TaLs) are also designed. Codes and Instructions for each TaL is provided on the book website, and accompanied by videos to facilitate their learning process.

Explainable Edge AI: A Futuristic Computing Perspective

Aboul Ella Hassanien,Deepak Gupta,Anuj Kumar Singh,Ankit Garg
Explainable Edge AI A Futuristic Computing Perspective Book PDF

Author : Aboul Ella Hassanien,Deepak Gupta,Anuj Kumar Singh,Ankit Garg
Publisher : Springer Nature
Page : 187 pages
File Size : 48,5 Mb
Release : 2022-11-10
Category : Technology & Engineering
ISBN : 9783031182921

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Explainable Edge AI: A Futuristic Computing Perspective by Aboul Ella Hassanien,Deepak Gupta,Anuj Kumar Singh,Ankit Garg Pdf

This book presents explainability in edge AI, an amalgamation of edge computing and AI. The issues of transparency, fairness, accountability, explainability, interpretability, data-fusion, and comprehensibility that are significant for edge AI are being addressed in this book through explainable models and techniques. The concept of explainable edge AI is new in front of the academic and research community, and consequently, it will undoubtedly explore multiple research dimensions. The book presents the concept of explainability in edge AI which is the amalgamation of edge computing and AI. In the futuristic computing scenario, the goal of explainable edge AI will be to execute the AI tasks and produce explainable results at the edge. First, this book explains the fundamental concepts of explainable artificial intelligence (XAI), then it describes the concept of explainable edge AI, and finally, it elaborates on the technicalities of explainability in edge AI. Owing to the quick transition in the current computing scenario and integration with the latest AI-based technologies, it is significant to facilitate people-centric computing through explainable edge AI. Explainable edge AI will facilitate enhanced prediction accuracy with the comprehensible decision and traceability of actions performed at the edge and have a significant impact on futuristic computing scenarios. This book is highly relevant to graduate/postgraduate students, academicians, researchers, engineers, professionals, and other personnel working in artificial intelligence, machine learning, and intelligent systems.

Advances in Edge Computing: Massive Parallel Processing and Applications

F. Xhafa,A.K. Sangaiah
Advances in Edge Computing Massive Parallel Processing and Applications Book PDF

Author : F. Xhafa,A.K. Sangaiah
Publisher : IOS Press
Page : 326 pages
File Size : 43,9 Mb
Release : 2020-03-10
Category : Computers
ISBN : 9781643680637

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Advances in Edge Computing: Massive Parallel Processing and Applications by F. Xhafa,A.K. Sangaiah Pdf

The rapid advance of Internet of Things (IoT) technologies has resulted in the number of IoT-connected devices growing exponentially, with billions of connected devices worldwide. While this development brings with it great opportunities for many fields of science, engineering, business and everyday life, it also presents challenges such as an architectural bottleneck – with a very large number of IoT devices connected to a rather small number of servers in Cloud data centers – and the problem of data deluge. Edge computing aims to alleviate the computational burden of the IoT for the Cloud by pushing some of the computations and logics of processing from the Cloud to the Edge of the Internet. It is becoming commonplace to allocate tasks and applications such as data filtering, classification, semantic enrichment and data aggregation to this layer, but to prevent this new layer from itself becoming another bottleneck for the whole computing stack from IoT to the Cloud, the Edge computing layer needs to be capable of implementing massively parallel and distributed algorithms efficiently. This book, Advances in Edge Computing: Massive Parallel Processing and Applications, addresses these challenges in 11 chapters. Subjects covered include: Fog storage software architecture; IoT-based crowdsourcing; the industrial Internet of Things; privacy issues; smart home management in the Cloud and the Fog; and a cloud robotic solution to assist medical applications. Providing an overview of developments in the field, the book will be of interest to all those working with the Internet of Things and Edge computing.