Abstract

Cloud computing has become a very hot topic over the past few years. One of the main requirements in cloud computing environments is a high degree of automation for provisioning and dynamic management of IT resources (compute, storage and network resources) and services. Also, in cloud computing environments composed of large virtualized datacenters, energy consumption and carbon footprint have become major concerns which significantly impact resource management. This special issue is based on extended versions of the Green and Cloud Management workshop (CGM 2012) which focused on management and control issues related to dependability, scalabilitity, performance and configuration at each level of cloud computing infrastructures, but also on green computing issues in such environments such as energy efficiency, carbon footprint reduction and cooling. This raises the issue of management automation for multi-criteria optimization (including green metrics) at each level of a cloud environment. Topics of interest addressed by this special issue include: Monitoring for Green and Cloud computing Control algorithms and policies for Green and Cloud computing Autonomic Computing applyied to Green and Cloud Computing Design of energy efficient cloud stacks Green-oriented Autonomic computing QoS and Green computing models for Clouds Energy efficiency benchmarking and profiling for Clouds Energy-aware configuration and resource management for Clouds Component model for cloud and green computing Software engineering methodologies and tools for cloud and green computing Scalability and reliability of management software for Green and Cloud computing Reporting and exposing carbon and energy impact Green architectures for Grids, Clouds and clusters Design of green computing middleware Green-aware configuration and resource management Scheduling and control in green computing Control and optimization techniques for green computing Real life experiments . This issue gathers papers which focus on : (i) processors and routers management ranging from thermal awareness to power control and DVFS techniques, (ii) coarce grain control in the case of cloud infrastructures using discrete controller synthesis or neural predictor, (iii) fine grain energy profiler which can be used to understand the energy consumption of a software stack. We would like to thank the program committee members for their help during the reviewing process. We are also thankful to the OSR editors for their help about this special issue. We hope you will enjoy this special issue so that the presented papers will help you opening perspectives for your future researches.

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