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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Proceedings ArticleDOI
Evaluation of SLA-based decision strategies for VM scheduling in cloud data centers
TL;DR: There are considerable differences between the scheduling strategies in terms of SLA violations and the number of migrations and the combination of the Minimization of Migrations strategy for VM selection and the Worst Fit strategy for host selection achieves the best results.
Proceedings ArticleDOI
A time-predictable fog-integrated cloud framework: One step forward in the deployment of a smart factory
Hamid Reza Faragardi,Saeid Dehnavi,Mehdi Kargahi,Alessandro Vittorio Papadopoulos,Thomas Nolte +4 more
TL;DR: A time-predictable cloud framework is proposed which is able to satisfy end-to-end latency requirements in a smart factory and not only uses existing real-time technologies such as Industrial Ethernet and the Real-time XEN hypervisor but also discusses unaddressed challenges.
Proceedings ArticleDOI
The impact of time of use (ToU)-awareness in energy and opex performance of a cloud backbone
TL;DR: Numerical results approve that Opex savings through ToU-aware provisioning are at the expense of increased delay per demand, and power-minimized provisioning introduces more savings to the network operator as upstream data center demands are transported towards the data centers at the off-peak locations, which in return leads to higher utilization of network components in longer routes.
Journal ArticleDOI
Carbon-Efficient Virtual Machine Placement Based on Dynamic Voltage Frequency Scaling in Geo-Distributed Cloud Data Centers
TL;DR: This research work proposes two DVFS-enabled host selection algorithms for virtual machine (VM) placement with a cluster selection strategy, namely the carbon and power-efficient optimal frequency (C-PEF) algorithm and the carbon-aware first-fit optimal frequency [C-FFF] algorithm.
Journal ArticleDOI
A memetic grouping genetic algorithm for cost efficient VM placement in multi-cloud environment
TL;DR: This paper proposes a correlation aware virtual machine placement algorithm, namely MGGAVP, based on the hybridization of the Grouping Genetic Algorithm and Hill-climbing and extended for the multi-cloud environment with target of minimizing the energy cost of allocated network elements.
References
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A view of cloud computing
Michael Armbrust,Armando Fox,Rean Griffith,Anthony D. Joseph,Randy H. Katz,Andy Konwinski,Gunho Lee,David A. Patterson,Ariel Rabkin,Ion Stoica,Matei Zaharia +10 more
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TL;DR: This paper defines Cloud computing and provides the architecture for creating Clouds with market-oriented resource allocation by leveraging technologies such as Virtual Machines (VMs), and provides insights on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain Service Level Agreement (SLA) oriented resource allocation.
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CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms
TL;DR: The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns.
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Live migration of virtual machines
Christopher Clark,Keir Fraser,Steven Hand,Jacob Gorm Hansen,Eric Jul,Christian Limpach,Ian Pratt,Andrew Warfield +7 more
TL;DR: The design options for migrating OSes running services with liveness constraints are considered, the concept of writable working set is introduced, and the design, implementation and evaluation of high-performance OS migration built on top of the Xen VMM are presented.
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