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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Journal ArticleDOI
Energy Optimization for Data Allocation With Hybrid SRAM+NVM SPM
TL;DR: This paper adopts CMP systems with hybrid scratchpad memories (SPMs) with hybrid SPM architecture, which are configured from SRAM and nonvolatile memory, and proposes two novel algorithms, i.e., energy-aware data allocation (EADA) and balancing data allocation to energy and write operations (BDAEW), to reduce energy consumption and latency.
Energy efficiency embedded service lifecycle: Towards an energy efficient cloud computing architecture
Karim Djemame,Django Armstrong,Richard Kavanagh,Ana Juan Ferrer,David Garcia Perez,David Antona,Jean-Christophe Deprez,Christophe Ponsard,David Ortiz,Mario Macías Lloret,Jordi Guitart Fernández,Francesc-Josep Lordan Gomis,Jorge Ejarque,Raül Sirvent Pardell,Rosa Maria Badia Sala,Michael Kammer,Odej Kao,Eleni Agiatzidou,Antonis Dimakis,Costas Courcoubetis,Lorenzo Blasi +20 more
TL;DR: The paper argues the need to provide novel methods and tools to support software developers aiming to optimise energy efficiency and minimise the carbon footprint resulting from designing, developing, deploying and running software in Clouds, while maintaining other quality aspects of software to adequate and agreed levels.
Proceedings Article
2-phase optimization method for energy aware scheduling of virtual machines in cloud data centers
TL;DR: The researchers tried to reduce energy consumed in Cloud computing datacenters by revising virtual machines scheduling method while keeping quality of service parameters as high as possible by reduction in number of virtual machines migrations.
Journal ArticleDOI
Energy-efficient Nature-Inspired techniques in Cloud computing datacenters
Mohammed Joda Usman,Abdul Samad Ismail,Gaddafi Abdul-Salaam,Hassan Chizari,Omprakash Kaiwartya,Abdulsalam Ya'u Gital,Muhammed Gambo Abdullahi,Ahmed Aliyu,Salihu Idi Dishing +8 more
TL;DR: A comprehensive review of the state-of-the-art Nature-Inspired algorithms suggested for solving the energy issues in the Cloud datacenters, focusing on three key dimension in the literature including virtualization, consolidation, and energy-awareness.
Journal ArticleDOI
Energy-efficient migration techniques for cloud environment: a step toward green computing
TL;DR: A thorough study of the various techniques that help in minimization of energy consumption in data centers is conducted and approaches to reduce the same are proposed, eventually making the environment greener.
References
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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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