Bio-Inspired Optimization in Fog and Edge Computing Environments

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B01=Dinesh Kumar Saini
B01=Kashif Zia
B01=Pradeep Rawat
B01=Punit Gupta
bio-inspired resource allocation in fog computing
Category1=Non-Fiction
Category=UB
Category=UK
Category=UKL
Category=UMB
Category=UTC
Category=UYQ
Cloud Computing
Cloud Data Centres
Cloud Environment
Cloud Node
Cloud Resource Management
Cloud Service Providers
cognitive traffic analytics
complex systems optimization
COP=United Kingdom
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distributed computing
Edge Computing
Edge Devices
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eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
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Fog
Fog Computing
Fog Devices
Fog Layer
Fog Network
GIS healthcare analytics
healthcare informatics
Internet of Things
IoT
IoT Application
IoT Device
IoT Network
IoT System
IoT Technology
Language_English
Ml Model
PA=Available
Parallel PSO
Power Consumption
Price_€50 to €100
PS=Active
resource management
SDSS
self-organizing algorithms
Service Oriented Computing Paradigm
Smart Health Care
softlaunch
swarm intelligence methods
systems complexity
virtualization in distributed networks

Product details

  • ISBN 9781032345895
  • Weight: 500g
  • Dimensions: 156 x 234mm
  • Publication Date: 09 Oct 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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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.

Dr. Punit Gupta is currently working as associate professor in the department of computer and communication engineering at Manipal University Jaipur, India.

Dr. Dinesh Kumar Saini is a full professor at the School of Computing and Information Technology, Manipal University.

Dr. Pradeep Rawat is affiliated with DIT University, India.

Dr. Kashif Zia is currently working as an associate professor in the faculty of computing and information technology, Sohar University, Oman.