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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Evaluating the cooling and computing energy demand of a datacentre with optimal server provisioning
TL;DR: A holistic model for the energy consumption of the server room that depends on user workload and service level agreement constraints, and that considers both cooling and computing energy dissipation is developed.
Journal ArticleDOI
Efficient multistage bandwidth allocation technique for virtual machine migration in cloud computing
Aditya Bhardwaj,C. Rama Krishna +1 more
Journal ArticleDOI
An Experience-Based Scheme for Energy-SLA Balance in Cloud Data Centers
TL;DR: This paper proposes several heuristic strategies to optimize these two metrics based on a two-level management model under a heterogeneous cloud environment, and proposes a weighted priority virtual machine selection algorithm for each VM on the overloaded host.
Journal ArticleDOI
Minimizing latency in geo-distributed clouds
TL;DR: This paper proposes an algorithm to minimize communication latency by taking into account the cloud network topology to be either a tree or that of the Internet, and shows that the algorithm performs well in the Internet topology.
Journal ArticleDOI
MAS-based self-adaptive architecture for controlling and monitoring Cloud platforms
TL;DR: An architecture to model the control and monitoring system of a Cloud Computing platform by using a Virtual Organization of intelligent agents that self-adapt and reorganize according to the needs of the surrounding environment is presented.
References
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Christopher Clark,Keir Fraser,Steven Hand,Jacob Gorm Hansen,Eric Jul,Christian Limpach,Ian Pratt,Andrew Warfield +7 more
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