Autonomic computing in cloud resource management in Industry 4.0 / / Tanupriya Choudhury [and five others] editors

• Record Nr.: UNINA9910495241503321
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2021]; ©2021
• ISBN: 3-030-71756-9
• Edizione: [1st ed. 2021.]
• Descrizione fisica: 1 online resource (XVI, 409 p. 135 illus. in color.)
• Collana: EAI/Springer Innovations in Communication and Computing
• Disciplina: 004
• Soggetti: Autonomic computing; Cloud computing; Industry 4.0
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Introduction -- Introduction to Cloud Resource Management -- Autonomic Computing in Cloud -- Model, and Applications -- Issues and challenges in Autonomic computing and resource management -- The architecture of Autonomic Cloud Resource Management -- A self-adaptable framework to find best optimization techniques -- Healing application against resource failure -- Modelling re-installation components to adapt system configuration -- Self-protection application to defend the malicious request -- Resource management system for scheduling -- Comparative Analysis of various autonomic management systems in the cloud -- Applicability of Autonomic computing in resource management -- Conclusion.
• Sommario/riassunto: This book describes the next generation of industry—Industry 4.0—and how it holds the promise of increased flexibility in manufacturing, along with automation, better quality, and improved productivity. The authors discuss how it thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. The authors posit that intelligent cloud services and resource sharing play an important role in Industry 4.0 anticipated Fourth Industrial Revolution. This book serves the different issues and challenges in cloud resource management CRM ; techniques with proper propped solution for IT organizations. The book features chapters based on the characteristics of autonomic computing with its applicability in CRM. Each chapter features the techniques and analysis of each mechanism to make better resource management in cloud. Describes self-adaptable framework to find the best optimization techniques automatically based on issues and platforms; Presents a self-optimized model to find the optimal resource from the resource pool; Includes applications to diagnose and heal the system failure, and protect from malicious attacks.