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Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032345896 ISBN 13: 9781032345895
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In den WarenkorbPaperback. Zustand: new. Paperback. 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. The book examines the enhancement of the performance of fog networks for real-world applications using nature-based optimization techniques. It looks at the challenges in cloud datacenter nodes and fog computing networks and provides solutions. It covers such issues as security, privacy, and power consumption. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032345896 ISBN 13: 9781032345895
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In den WarenkorbPaperback. Zustand: new. Paperback. 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. The book examines the enhancement of the performance of fog networks for real-world applications using nature-based optimization techniques. It looks at the challenges in cloud datacenter nodes and fog computing networks and provides solutions. It covers such issues as security, privacy, and power consumption. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032345896 ISBN 13: 9781032345895
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: new. Paperback. 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. The book examines the enhancement of the performance of fog networks for real-world applications using nature-based optimization techniques. It looks at the challenges in cloud datacenter nodes and fog computing networks and provides solutions. It covers such issues as security, privacy, and power consumption. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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In den WarenkorbGebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.