A new era of complexity science is emerging, in which nature- and bio-inspired principles are being applied to provide solutions. At the same time, the complexity of systems is increasing due to such models like the Internet of Things (IoT) and fog computing. Will complexity science, applying the principles of nature, be able to tackle the challenges posed by highly complex networked systems?

Bio-Inspired Optimization in Fog and Edge Computing: Principles, Algorithms, and Systems is an attempt to answer this question. It presents innovative, bio-inspired solutions for fog and edge computing and highlights the role of machine learning and informatics. Nature- or biological-inspired techniques are successful tools to understand and analyze a collective behavior. As this book demonstrates, algorithms, and mechanisms of self-organization of complex natural systems have been used to solve optimization problems, particularly in complex systems that are adaptive, ever-evolving, and distributed in nature.

The chapters look at ways of enhancingto enhance the performance of fog networks in real-world applications using nature-based optimization techniques. They discuss challenges and provide solutions to the concerns of security, privacy, and power consumption in cloud data center nodes and fog computing networks. The book also examines how:

The existing fog and edge architecture is used to provide solutions to future challenges.
A geographical information system (GIS) can be used with fog computing to help users in an urban region access prime healthcare.
An optimization framework helps in cloud resource management.
Fog computing can improve the quality, quantity, long-term viability, and cost-effectiveness in agricultural production.
Virtualization can support fog computing, increase resources to be allocated, and be applied to different network layers.
The combination of fog computing and IoT or cloud computing can help healthcare workers predict and analyze diseases in patients.

Frequently asked questions

Simply head over to the account section in settings and click on “Cancel Subscription” - it’s as simple as that. After you cancel, your membership will stay active for the remainder of the time you’ve paid for. Learn more here.

At the moment all of our mobile-responsive ePub books are available to download via the app. Most of our PDFs are also available to download and we're working on making the final remaining ones downloadable now. Learn more here.

Both plans give you full access to the library and all of Perlego’s features. The only differences are the price and subscription period: With the annual plan you’ll save around 30% compared to 12 months on the monthly plan.

We are an online textbook subscription service, where you can get access to an entire online library for less than the price of a single book per month. With over 1 million books across 1000+ topics, we’ve got you covered! Learn more here.

Look out for the read-aloud symbol on your next book to see if you can listen to it. The read-aloud tool reads text aloud for you, highlighting the text as it is being read. You can pause it, speed it up and slow it down. Learn more here.

Yes, you can access Bio-Inspired Optimization in Fog and Edge Computing Environments by Punit Gupta, Dinesh Kumar Saini, Pradeep Rawat, Kashif Zia in PDF and/or ePUB format, as well as other popular books in Computer Science & Cloud Computing. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Auerbach Publications

Year

2023

ISBN

9781000811544

Edition

Topic

Computer Science

Subtopic

Cloud Computing

Index

Computer Science

Cover
Half-Title Page
Title Page
Copyright Page
Table of Contents
Preface
List of Editors
List of Contributors
Chapter 1 Introduction to Optimization in Fog Computing
Chapter 2 Open Issues and Challenges in Fog and Edge
Chapter 3 Future Challenges in Fog and Edge Computing Applications
Chapter 4 Geographic Information Systems-Based Modeling of Health Care Data and its Optimization Using Various Approaches
Chapter 5 Application of Optimization Techniques in Cloud Resource Management
Chapter 6 Use of Fog Computing in Health Care
Chapter 7 Fog Computing for Agriculture Applications and its Issues
Chapter 8 Fog Computing and Vehicular Networks for Smart Traffic Control: Fog Computing-Based Cognitive Analytics Model for Smart Traffic Control
Chapter 9 Virtualization Concepts and Industry Standards in Cloud Computing
Chapter 10 Optimized Cloud Storage Data Analysis Using the Machine Learning Model
Chapter 11 Resource Management in Fog Computing Environment Using Optimal Fog Network Topology
Chapter 12 Applications of Fog in Healthcare Services
Chapter 13 Roles and Future of the Internet of Things-Based Smart Health Care Models
Index