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Virtualized Cloud Data Center Networks: Issues in Resource Management. / by Linjiun Tsai, Wanjiun Liao

By: Tsai, Linjiun.
Contributor(s): Liao, Wanjiun | SpringerLink (Online service)
Material type: materialTypeLabelE-bookSeries: (SpringerBriefs in Electrical and Computer Engineering, 2191-8112).Publisher: Cham : Springer International Publishing, 2016Description: 1 recurso en línea (VIII, 57 páginas) : 21 ilustraciones.ISBN: 9783319326320.Subject: Informática en la nube | InformáticaDDC classification: 621.382 Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Introduction -- Allocation of Virtual Machines -- Transformation of Data Center Networks -- Allocation of Servers -- Performance Evaluation -- Conclusion. .
Summary: This book discusses the characteristics of virtualized cloud networking, identifies the requirements of cloud network management, and illustrates the challenges in deploying virtual clusters in multi-tenant cloud data centers. The book also introduces network partitioning techniques to provide contention-free allocation, topology-invariant reallocation, and highly efficient resource utilization, based on the Fat-tree network structure. Managing cloud data center resources without considering resource contentions among different cloud services and dynamic resource demands adversely affects the performance of cloud services and reduces the resource utilization of cloud data centers. These challenges are mainly due to strict cluster topology requirements, resource contentions between uncooperative cloud services, and spatial/temporal data center resource fragmentation. Cloud data center network resource allocation/reallocation which cope well with such challenges will allow cloud services to be provisioned with predictable network performance, mitigate service performance degradation and even guarantee service level agreements. Virtualized Cloud Data Center Networks: Issues in Resource Management tackles the challenges of managing cloud data center networks and introduces techniques to efficiently deploy large-scale distributed computing applications that require predictable performance in multi-tenant cloud data centers. .
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA76.585 .T73 2016 EB (Browse shelf(Opens below)) .i11614675 Acceso electrónico eBOOK .i11614675
Total holds: 0

Introduction -- Allocation of Virtual Machines -- Transformation of Data Center Networks -- Allocation of Servers -- Performance Evaluation -- Conclusion. .

This book discusses the characteristics of virtualized cloud networking, identifies the requirements of cloud network management, and illustrates the challenges in deploying virtual clusters in multi-tenant cloud data centers. The book also introduces network partitioning techniques to provide contention-free allocation, topology-invariant reallocation, and highly efficient resource utilization, based on the Fat-tree network structure. Managing cloud data center resources without considering resource contentions among different cloud services and dynamic resource demands adversely affects the performance of cloud services and reduces the resource utilization of cloud data centers. These challenges are mainly due to strict cluster topology requirements, resource contentions between uncooperative cloud services, and spatial/temporal data center resource fragmentation. Cloud data center network resource allocation/reallocation which cope well with such challenges will allow cloud services to be provisioned with predictable network performance, mitigate service performance degradation and even guarantee service level agreements. Virtualized Cloud Data Center Networks: Issues in Resource Management tackles the challenges of managing cloud data center networks and introduces techniques to efficiently deploy large-scale distributed computing applications that require predictable performance in multi-tenant cloud data centers. .

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