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
Figures
Fig. 10. The network optimization. 
Fig. 11. The temperature optimization. 
Fig. 9. The optimization over multiple resources. 
Fig. 3. The mean energy consumption by the MM policy for different values of the utilization thresholds. 
Fig. 2. The energy consumption and SLA violations by the ST policy. 
Fig. 8. The distribution of the time until a host is switched to the sleep mode.
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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Journal ArticleDOI
Security and privacy threats to volunteer computing
TL;DR: This paper presents security and privacy threat taxonomy along with the security features developed to cope with such threats.
Proceedings ArticleDOI
Multi-Cluster Computing Interconnection Network Performance Modeling and Analysis
TL;DR: This paper addresses the problem of fat-tree based interconnection networks performance modeling for multi-user heterogeneous multi-cluster computing systems and presents an analytical model and validate the model through comprehensive simulation.
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