Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing
TLDR
An architectural framework and principles for energy-efficient Cloud computing are defined and the proposed energy-aware allocation heuristics provision data center resources to client applications in a way that improves energy efficiency of the data center, while delivering the negotiated Quality of Service (QoS).About:
This article is published in Future Generation Computer Systems.The article was published on 2012-05-01 and is currently open access. It has received 2511 citations till now. The article focuses on the topics: Cloud computing & Utility computing.read more
Citations
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A Survey on Mobile Edge Computing: The Communication Perspective
TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management is provided in this paper, where a set of issues, challenges, and future research directions for MEC are discussed.
Posted Content
A Survey on Mobile Edge Computing: The Communication Perspective
TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management and recent standardization efforts on MEC are introduced.
Journal ArticleDOI
Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers
Anton Beloglazov,Rajkumar Buyya +1 more
TL;DR: A competitive analysis is conducted and competitive ratios of optimal online deterministic algorithms for the single VM migration and dynamic VM consolidation problems are proved, and novel adaptive heuristics for dynamic consolidation of VMs are proposed based on an analysis of historical data from the resource usage by VMs.
Journal ArticleDOI
Data Center Energy Consumption Modeling: A Survey
TL;DR: An in-depth study of the existing literature on data center power modeling, covering more than 200 models, organized in a hierarchical structure with two main branches focusing on hardware-centric and software-centric power models.
Journal ArticleDOI
On Global Electricity Usage of Communication Technology: Trends to 2030
Anders S. G. Andrae,Tomas Edler +1 more
TL;DR: An estimation of the global electricity usage that can be ascribed to Communication Technology between 2010 and 2030 suggests that CT electricity usage could contribute up to 23% of the globally released greenhouse gas emissions in 2030.
References
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Proceedings ArticleDOI
Optimal power allocation in server farms
TL;DR: The analysis shows that the optimal power allocation is non-obvious and depends on many factors such as the power-to-frequency relationship in the processors, the arrival rate of jobs, the maximum server frequency, the lowest attainable server frequency and the server farm configuration.
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Smart cooling of data centers
TL;DR: In this paper, a cooling system is configured to adjust cooling fluid flow to various racks located throughout a data center based upon the detected or anticipated temperatures at various locations throughout the data center.
Proceedings Article
Energy-efficient management of data center resources for cloud computing : a vision, architectural elements, and open challenges
TL;DR: In this paper, the authors present vision, challenges, and architectural elements for energy-efficient management of cloud computing environments, focusing on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures and holistically work to boost data center energy efficiency and performance.
Proceedings ArticleDOI
Shares and utilities based power consolidation in virtualized server environments
TL;DR: This work presents a novel suite of techniques for placement and power consolidation of VMs in data centers taking advantage of the min-max and shares features inherent in virtualization technologies, and provides a smooth mechanism for power-performance tradeoffs in modern data centers running heterogeneous applications.
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Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers
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