Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications

Deepak Gupta, Aditya Khamparia, Deepak Gupta, Aditya Khamparia

• Publisher: Wiley-IEEE Press
• Year: 2020
• Print ISBN: 9781119670070
• eBook ISBN: 9781119670100
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Electrical Engineering & Telecommunications
• Index: Technology & Engineering

A practical guide to the design, implementation, evaluation, and deployment of emerging technologies for intelligent IoT applications

With the rapid development in artificially intelligent and hybrid technologies, IoT, edge, fog-driven, and pervasive computing techniques are becoming important parts of our daily lives. This book focuses on recent advances, roles, and benefits of these technologies, describing the latest intelligent systems from a practical point of view. Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications is also valuable for engineers and professionals trying to solve practical, economic, or technical problems. With a uniquely practical approach spanning multiple fields of interest, contributors cover theory, applications, and design methodologies for intelligent systems. These technologies are rapidly transforming engineering, industry, and agriculture by enabling real-time processing of data via computational, resource-oriented metaheuristics and machine learning algorithms. As edge/fog computing and associated technologies are implemented far and wide, we are now able to solve previously intractable problems. With chapters contributed by experts in the field, this book:

• Describes Machine Learning frameworks and algorithms for edge, fog, and pervasive computing
• Considers probabilistic storage systems and proven optimization techniques for intelligent IoT
• Covers 5G edge network slicing and virtual network systems that utilize new networking capacity
• Explores resource provisioning and bandwidth allocation for edge, fog, and pervasive mobile applications
• Presents emerging applications of intelligent IoT, including smart farming, factory automation, marketing automation, medical diagnosis, and more

Researchers, graduate students, and practitioners working in the intelligent systems domain will appreciate this book's practical orientation and comprehensive coverage. Intelligent IoT is revolutionizing every industry and field today, and Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications provides the background, orientation, and inspiration needed to begin.

1
Fog, Edge and Pervasive Computing in Intelligent Internet of Things Driven Applications in Healthcare: Challenges, Limitations and Future Use

Afroj Alam¹, Sahar Qazi², Naiyar Iqbal³, and Khalid Raza²*

¹Department of Computer Science, Integral University, Lucknow, India

²Department of Computer Science, Jamia Millia Islamia, New Delhi

³Department of Computer Science and IT, Maulana Azad National Urdu University, Hyderabad

Abstract

The Internet of Things (IoT), fog, edge and pervasive computing are all emerging technologies, which have several promising applications including healthcare. This technology is witnessing a paradigm shift in the healthcare sector, moving out from traditional ways of visiting hospitals. It connects the doctors, patients, and nurses through smart intelligent sensor devices at low cost with high bandwidth networks. In this chapter, we discuss these new computing paradigms precisely and present their applications in ubiquitous healthcare. This chapter also covers various problems and challenges that have been faced by practitioners in the last few years in the field of cloud computing and the IoT that have been solved by fog, edge and pervasive computing.

Keywords: Fog Computing; Edge Computing; Pervasive Computing; IoT; Healthcare;

1.1 Introduction

Today, the Internet of Things (IoT), fog, edge and pervasive computing are buzzwords, which have pivotal applications in different fields of studies including healthcare, engineering, and other intelligent applications. Cloud computing and the IoT have emerged as a new paradigm in the field of information and communication technology (ICT) as a revolution of the 21st century. It was a long‐awaited dream of to use computing as a utility. Traditional computing extends the model to a cloud computing paradigm which has the capability to renovate a huge portion of the information technology industry, making the software even more interesting as a service that customers can access on‐demand. The IoT acts as an interconnection between various gadgets and the Internet, including mobile phones, vehicles, farms, factories, home automation systems, and wearable devices from the viewpoint of the enhancement of the competence of real‐life computing usage. This new technology, especially in the healthcare sector, is a change from the conventional approach of visiting clinics or hospitals. It links doctors, patients, and nurses by means of intelligent, affordable sensor gadgets with the support of cloud computing (Qi et al., 2019). Unfortunately, a number of IoT based intelligent sensor gadgets are developing at a rapid rate. On the basis of evaluation, if the pace of extension proceeds constantly from 2020, the number of wearable gadgets on the planet will reach to around 26 billion (Imran and Qadeer, 2019). The volume of data generated using these IoT gadgets is very large. The capability of the present cloud model is not adequate to deal with the requirements of the IoT, i.e., the current cloud has issues regarding volume, latency, and bandwidth. The current cloud cannot fulfill every one of the prerequisites of QoS (Quality of Service) in the IoT, therefore the goal is that another framework, fog computing, is introduced that will solve the issues of volume, latency and bandwidth (Shi et al., 2015).

Fog computing has appeared with a new computation model which is placed between the cloud and intelligence sensor‐based IoT devices through which an assortment of heterogeneous gadgets are pervasively associated as the terminal of a network which provides communication facilities to ease the execution of relevant IoT services (Chang et al., 2019). Fog computing covers the cloud computing approach in the direction of the edge of the network, which has many advantages over cloud computing. Fog computing is appropriate for the applications by which real‐time, high response time, and less latency are important issues, specifically in healthcare utilization (Mutlag et al., 2019). It is enabling new or mutated applications and facilities with a productive transaction between cloud and fog, especially with the issues of volume, latency, and bandwidth regarding data management (JoSEP et al., 2010).

In this chapter, we propose to explain new trends of computing models to understand the evolving IoT applications, exclusively fog and edge computing, their background, features, model architecture and current challenges. This chapter also covers various problems and challenges that have been faced by the practitioners in previous years in the field of cloud computing associated with the IoT that has been solved by fog, edge and pervasive computing (De Donno et al., 2019). Further, because the Cybercrime Report 2016 suggests that cybercrime damages will be around $6 trillion every year by 2021, up from $3 trillion in 2015 it will cover how to secure the privacy of IoT based sensor devices and private data in the cloud using machine learning. Further, we will demonstrate in this chapter that fog computing definitely reduces latency as opposed to cloud computing. The low latency is significant for the medical IoT framework because of real‐time requirements. Although the Cloud‐based IoT (CIoT) structure is a typical way to deal with executing IoT frameworks, it is, however, confronting developing difficulties in the IoT. Specifically, CIoT deals with current challenges such as data transmission rate, latency rate, interruption, limitation of resource and secure system. The developing difficulties of CIoT have brought up an issue – what is needed to conquer the barrier of current cloud‐driven architecture? Fog computing architecture is a visionary model that includes all probabilities to encompass the cloud to the edge network of CIoT, from the distant central cloud datacenter, the interim system hubs to the far edge where the front‐end IoT gadgets are situated.

1.2 Why Fog, Edge, and Pervasive Computing?

Fog Computing

Fog computing is a distributed paradigm that provides computation, storage and network facilities between client gadgets and cloud datacenters mostly but not specifically situated on edge networks (Inbaraj, 2020). In such a way a cloud‐based facility can be enlarged nearer to the IoT gadgets/centers. In this scenario, fog acts as a middle layer between IoT based sensor machines and cloud datacenters (Bangui et al., 2018). The idea of fog computing was first created by Cisco in 2012 to report the difficulties of the IoT applications in traditional cloud computing. The challenges of fog computing are the facilitation and enhancement of mobility, real‐time interaction, privacy, security, low latency, low energy consumption and network bandwidth for real‐life applications where we need a quick response from the cloud, especially in the healthcare sector.

One of the benefits of fog computing is that, in place of transferring the entire data of IoT devices to the cloud, the fog will filter the data and then send a summary of the data. Another benefit is that fog computing processes the data before transferring to the cloud and will lead to reducing the communication period rate along with reducing the requirement of storage of massive data at the cloud. The key role of fog computing is data gathering from IoT sensors gadgets, data processing, data filtering and then finally sending a summary of the data to the cloud (Mehdipour et al., 2019).

The Need for Fog Computing

Over the past decade, we have seen that the trend of storage, computing, controlling, and network management function over the data has been shifted from traditional computing to the cloud computing paradigm. On the basis of evaluation, if the pace of extension proceeds constantly from 2020, the number of wearable gadgets on the planet will reach around 26 billion (Im...

Table of contents

• Cover
• Table of Contents
• Fog, Edge, and Pervasive Computing in Intelligent IoT Driven Applications
• Copyright
• About the Editors
• List of Contributors
• Preface
• Acknowledgments
• 1 Fog, Edge and Pervasive Computing in Intelligent Internet of Things Driven Applications in Healthcare: Challenges, Limitations and Future Use
• 2 Future Opportunistic Fog/Edge Computational Models and their Limitations
• 3 Automating Elicitation Technique Selection using Machine Learning
• Chapter 4: Machine Learning Frameworks and Algorithms for Fog and Edge Computing
• Chapter 5: Integrated Cloud Based Library Management in Intelligent IoT driven Applications
• Chapter 6: A Systematic and Structured Review of Intelligent Systems for Diagnosis of Renal Cancer
• Chapter 7: Location Driven Edge Assisted Device and Solutions for Intelligent Transportation
• Chapter 8: Design and Simulation of MEMS for Automobile Condition Monitoring Using COMSOL Multiphysics Simulator
• Chapter 9: IoT Driven Healthcare Monitoring System
• Chapter 10: Fog Computing as Future Perspective in Vehicular Ad hoc Networks
• Chapter 11: An Overview to Design an Efficient and Secure Fog‐assisted Data Collection Method in the Internet of Things
• Chapter 12: Role of Fog Computing Platform in Analytics of Internet of Things‐ Issues, Challenges and Opportunities
• Chapter 13: A Medical Diagnosis of Urethral Stricture Using Intuitionistic Fuzzy Sets
• Chapter 14: Security Attacks in Internet of Things
• Chapter 15: Fog Integrated Novel Architecture for Telehealth Services with Swift Medical Delivery
• Chapter 16: Fruit Fly Optimization Algorithm for Intelligent IoT Applications
• Chapter 17: Optimization Techniques for Intelligent IoT Applications
• Chapter 18: Optimization Techniques for Intelligent IoT Applications in Transport Processes
• Chapter 19: Role of Intelligent IOT Applications in Fog paradigm: Issues, Challenges and Future Opportunities
• Chapter 20: Security and Privacy Issues in Fog/Edge/Pervasive Computing
• Chapter 21: Fog and Edge Driven Security & Privacy Issues in IoT Devices
• Index
• End User License Agreement