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Advanced Computing Techniques for Optimization in Cloud

Bag om Advanced Computing Techniques for Optimization in Cloud

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. 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 meta-heuristic 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.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9781032600079
  • Indbinding:
  • Hardback
  • Udgivet:
  • 11. september 2024
  • Størrelse:
  • 156x234x16 mm.
  • Vægt:
  • 544 g.
  • 2-4 uger.
  • 28. december 2024
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Forlænget returret til d. 31. januar 2025

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Beskrivelse af Advanced Computing Techniques for Optimization in Cloud

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. 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 meta-heuristic 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.

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