Advanced Computing Techniques Optimization Cloud (26 results)

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New. Dr. Madhusudhan H S is currently working as Associate Professor in the Department of computer science and Engineering at Vidyavardhaka College of Engineering, Mysuru, Karnataka, India. He has published scientific research publications in reputed I.

Taschenbuch. Condition: Neu. Neuware - This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques. - Focuses on virtual machine placement and migration techniques for cloud data centers - Presents the role of machine learning and metaheuristic approaches for optimisation in cloud computing services - Includes application of placement techniques for quality of service, performance, and reliability improvement - Explores data center resource management, load balancing and orchestration using machine learning techniques - Analyses dynamic and scalable resource scheduling with a focus on resource management The text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology.…

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New. pp. 248.

Condition: New.

Condition: New. pp. 248 1st Editin NO-PA16APR2015-KAP.

Condition: New.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New. pp. 248.

Hardback. Condition: New. New copy - Usually dispatched within 4 working days.

Condition: New. In English.

Hardback. Condition: New. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.Focuses on virtual machine placement and migration techniques for cloud data centersPresents the role of machine learning and metaheuristic approaches for optimisation in cloud computing servicesIncludes application of placement techniques for quality of service, performance, and reliability improvementExplores data center resource management, load balancing and orchestration using machine learning techniquesAnalyses dynamic and scalable resource scheduling with a focus on resource managementThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology.…

Hardcover. Condition: Brand New. 280 pages. French language. 9.18x6.12x8.66 inches. In Stock.

Hardback. Condition: New. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.Focuses on virtual machine placement and migration techniques for cloud data centersPresents the role of machine learning and metaheuristic approaches for optimisation in cloud computing servicesIncludes application of placement techniques for quality of service, performance, and reliability improvementExplores data center resource management, load balancing and orchestration using machine learning techniquesAnalyses dynamic and scalable resource scheduling with a focus on resource managementThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology.…

hardcover. Condition: Fine.

Paperback. Condition: new. Paperback. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.Focuses on virtual machine placement and migration techniques for cloud data centersPresents the role of machine learning and metaheuristic approaches for optimisation in cloud computing servicesIncludes application of placement techniques for quality of service, performance, and reliability improvementExplores data center resource management, load balancing and orchestration using machine learning techniquesAnalyses dynamic and scalable resource scheduling with a focus on resource managementThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and meta-heuristic approaches for placement techniques. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.Focuses on virtual machine placement and migration techniques for cloud data centersPresents the role of machine learning and metaheuristic approaches for optimisation in cloud computing servicesIncludes application of placement techniques for quality of service, performance, and reliability improvementExplores data center resource management, load balancing and orchestration using machine learning techniquesAnalyses dynamic and scalable resource scheduling with a focus on resource managementThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and meta-heuristic approaches for placement techniques. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condition: new. Paperback. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.Focuses on virtual machine placement and migration techniques for cloud data centersPresents the role of machine learning and metaheuristic approaches for optimisation in cloud computing servicesIncludes application of placement techniques for quality of service, performance, and reliability improvementExplores data center resource management, load balancing and orchestration using machine learning techniquesAnalyses dynamic and scalable resource scheduling with a focus on resource managementThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and meta-heuristic approaches for placement techniques. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.Focuses on virtual machine placement and migration techniques for cloud data centersPresents the role of machine learning and metaheuristic approaches for optimisation in cloud computing servicesIncludes application of placement techniques for quality of service, performance, and reliability improvementExplores data center resource management, load balancing and orchestration using machine learning techniquesAnalyses dynamic and scalable resource scheduling with a focus on resource managementThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology. 264 pp. Englisch.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Madhusudhan H S is currently working as Associate Professor in the Department of computer science and Engineering at Vidyavardhaka College of Engineering, Mysuru, Karnataka, India. He has published scientific research publications in reputed I.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.Focuses on virtual machine placement and migration techniques for cloud data centersPresents the role of machine learning and metaheuristic approaches for optimisation in cloud computing servicesIncludes application of placement techniques for quality of service, performance, and reliability improvementExplores data center resource management, load balancing and orchestration using machine learning techniquesAnalyses dynamic and scalable resource scheduling with a focus on resource managementThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology.…