Advanced Computing Techniques for Optimization in Cloud
Book Details
Format
Paperback / Softback
ISBN-10
1032600098
ISBN-13
9781032600093
Publisher
Taylor & Francis Ltd
Imprint
Chapman & Hall/CRC
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jul 19th, 2026
Print length
248 Pages
Weight
480 grams
Product Classification:
Digital and Information technology: general topicsInformation technology: general issuesInternet guides & online servicesInternet guides and online servicesSupercomputersReal time operating systemsSoftware EngineeringComputer securityDistributed systemsDistributed systems / Distributed computingComputer architecture & logic designComputer architecture and logic designArtificial intelligenceArtificial intelligence (AI)
Ksh 9,900.00
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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 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.
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