Eevmc An Energy Efficient Virtual Machine Consolidation Approach For Cloud Data Centers
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Eevmc An Energy Efficient Virtual Machine Consolidation Approach For Cloud Data Centers
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Author : Attique Ur Rehman
language : en
Publisher: Infinite Study
Release Date : 2024-07-09
Eevmc An Energy Efficient Virtual Machine Consolidation Approach For Cloud Data Centers written by Attique Ur Rehman and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-09 with Mathematics categories.
The dynamic landscape of cloud computing design presents significant challenges regarding power consumption and quality of service (QoS). Virtual machine (VM) consolidation is essential for reducing power usage and enhancing QoS by relocating VMs between hosts. OpenStack Neat, a leading framework for VM consolidation, employs the Modified Best-Fit Decreasing (MBFD) VM placement technique, which faces issues related to energy consumption and QoS. To address these issues, we propose an Energy Efficient VM Consolidation (EEVMC) approach. Our method introduces a novel host selection criterion based on the incurred loss during VM placement to identify the most efficient host. For validation, we conducted simulations using real-time workload traces from Planet-Lab and Materna over ten days, leveraging the latest CloudSim toolkit to compare our approach with state-of-the-art techniques. For Planet-Lab’s workload, our EEVMC approach shows a reduction in energy consumption by 80.35%, 59.76%, 21.59%, and 7.40%, and fewer system-level agreement (SLA) violations by 94.51%, 94.85%, 47.17%, and 17.78% when compared to Modified Best-Fit Decreasing (MBFD), Power-Aware Best Fit Decreasing (PABFD), Medium Fit Power Efficient Decreasing (MFPED), and Power-Efficient Best-Fit Decreasing (PEBFD), respectively. Similarly, for Materna,EEVMCachieves a reduction in energy consumption by 16.10%, 61.0%, 4.94%, and 4.82%, and fewer SLA violations by 76.99%, 88.88%, 12.50%, and 48.65% against the same benchmarks. Additionally, Loss-Aware Performance Efficient Decreasing (LAPED) significantly reduces the total number of VM migrations and SLA time per active host, indicating a substantial improvement in cloud computing efficiency.
Utilization Prediction Aware Virtual Machine Consolidation Approach For Energy Efficient Cloud Data Centers
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Author : 劉政昇
language : en
Publisher:
Release Date : 2017
Utilization Prediction Aware Virtual Machine Consolidation Approach For Energy Efficient Cloud Data Centers written by 劉政昇 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Energy Efficiency In Data Centers And Clouds
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Author :
language : en
Publisher: Academic Press
Release Date : 2016-01-28
Energy Efficiency In Data Centers And Clouds written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-28 with Technology & Engineering categories.
Advances in Computers carries on a tradition of excellence, presenting detailed coverage of innovations in computer hardware, software, theory, design, and applications. The book provides contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles typically allow. The articles included in this book will become standard references, with lasting value in this rapidly expanding field. - Presents detailed coverage of recent innovations in computer hardware, software, theory, design, and applications - Includes in-depth surveys and tutorials on new computer technology pertaining to computing: combinatorial testing, constraint-based testing, and black-box testing - Written by well-known authors and researchers in the field - Includes extensive bibliographies with most chapters - Presents volumes devoted to single themes or subfields of computer science
Automatic And Energy Efficient Management Of Large Scale Virtualized Data Centers
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Author : Eugen Feller
language : en
Publisher:
Release Date : 2012
Automatic And Energy Efficient Management Of Large Scale Virtualized Data Centers written by Eugen Feller and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Large-scale virtualized data centers now require cloud providers to implement scalable, autonomic, and energy-efficient cloud management systems. To address these challenges this thesis proposes Snooze, a novel highly available, easy to configure, and energy-efficient Infrastructure-as-a-Service (IaaS) cloud management system. For scalability and high availability Snooze integrates a self-configuring and healing hierarchical architecture. To achieve energy efficiency Snooze integrates a holistic energy management approach via virtual machine (VM) resource utilization monitoring, server underload/overload mitigation, VM consolidation, and power management. A robust Snooze prototype was developed and extensively evaluated on the Grid'5000 testbed using realistic applications. The experiments have proven Snooze to be scalable, highly available and energy-efficient. One way to favor servers idle times in IaaS clouds is to perform energy-efficient VM placement and consolidation. This thesis proposes a novel VM placement algorithm based on the Ant Colony Optimization (ACO) meta-heuristic. Simulation results have shown that the proposed algorithm computes close to optimal solutions and outperforms the evaluated First-Fit Decreasing algorithm at the cost of decreased scalability. To enable scalable VM consolidation, this thesis makes two further contributions: (i) an ACO-based VM consolidation algorithm; (ii) a fully decentralized VM consolidation system based on an unstructured peer-to-peer network of servers. Emulation conducted on the Grid'5000 testbed has proven our system to be scalable as well as to achieve data center utilization close to the one of a centralized system.
The Green And Virtual Data Center
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Author : Greg Schulz
language : en
Publisher: CRC Press
Release Date : 2016-04-19
The Green And Virtual Data Center written by Greg Schulz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Business & Economics categories.
The Green and Virtual Data Center sets aside the political aspects of what is or is not considered green to instead focus on the opportunities for organizations that want to sustain environmentally-friendly economical growth. If you are willing to believe that IT infrastructure resources deployed in a highly virtualized manner can be combined with other technologies to achieve simplified and cost-effective delivery of services in a green, profitable manner, this book is for you. Savvy industry veteran Greg Schulz provides real-world insight, addressing best practices, server, software, storage, networking, and facilities issues concerning any current or next-generation virtual data center that relies on underlying physical infrastructures. Coverage includes: Energy and data footprint reduction, Cloud-based storage and computing, Intelligent and adaptive power management, Server, storage, and networking virtualization, Tiered servers and storage, network, and data centers, Energy avoidance and energy efficiency. Many current and emerging technologies can enable a green and efficient virtual data center to support and sustain business growth with a reasonable return on investment. This book presents virtually all critical IT technologies and techniques to discuss the interdependencies that need to be supported to enable a dynamic, energy-efficient, economical, and environmentally-friendly green IT data center. This is a path that every organization must ultimately follow. Take a tour of the Green and Virtual Data Center website. CRC Press is pleased to announce that The Green and Virtual Data Center has been added to Intel Corporation's Recommended Reading List. Intel's Recommended Reading program provides technical professionals a simple and handy reference list of what to read to stay abreast of new technologies. Dozens of industry technologists, corporate fellows, and engineers have helped by suggesting books and reviewing the list. This is the most comprehensive reading list available for professional computer developers.
Energy Efficient Management Of Virtual Machines In Data Centers For Cloud Computing
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Author : Anton Beloglazov
language : en
Publisher:
Release Date : 2013
Energy Efficient Management Of Virtual Machines In Data Centers For Cloud Computing written by Anton Beloglazov and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Cloud computing categories.
Energy Efficient Data Centers
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Author : Sonja Klingert
language : en
Publisher: Springer
Release Date : 2014-05-21
Energy Efficient Data Centers written by Sonja Klingert and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-21 with Computers categories.
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Energy Efficient Data Centers, E2DC 2013, held in Berkeley, CA, USA, in May 2013; co-located with SIGCOMM e-Energy 2013. The 8 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on energy and workload measurement; energy management; simulators and control.
Congestion Control Energy Efficiency And Virtual Machine Placement For Data Centers
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Author : Yan Zhang
language : en
Publisher:
Release Date : 2014
Congestion Control Energy Efficiency And Virtual Machine Placement For Data Centers written by Yan Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
Data centers, facilities with communications network equipment and servers for data processing and/or storage, are prevalent and essential to provide a myriad of services and applications for various private, non-profit, and government systems, and they also form the foundation of cloud computing, which is transforming the technological landscape of the Internet. With rapid deployment of modern high-speed low-latency large-scale data centers, many issues have emerged in data centers, such as data center architecture design, congestion control, energy efficiency, virtual machine placement, and load balancing. The objective of this thesis is multi-fold. First, an enhanced Quantized Congestion Notification (QCN) congestion notification algorithm, called fair QCN (FQCN), is proposed to improve rate allocation fairness of multiple flows sharing one bottleneck link in data center networks. Detailed analysis on FQCN and simulation results is provided to validate the fair share rate allocation while maintaining the queue length stability. Furthermore, the effects of congestion notification algorithms, including QCN, AF-QCN and FQCN, are investigated with respect to TCP throughput collapse. The results show that FQCN can significantly enhance TCP throughput performance, and achieve better TCP throughput than QCN and AF-QCN in a TCP Incast setting. Second, a unified congestion detection, notification and control system for data center networks is designed to efficiently resolve network congestion in a uniform solution and to ensure convergence to statistical fairness with "no state" switches simultaneously. The architecture of the proposed system is described in detail and the FQCN algorithm is implemented in the proposed framework. The simulation results of the FQCN algorithm implemented in the proposed framework validate the robustness and efficiency of the proposed congestion control system. Third, a two-level power optimization model, namely, Hierarchical EneRgy Optimization (HERO), is established to reduce the power consumption of data center networks by switching off network switches and links while still guaranteeing full connectivity and maximizing link utilization. The power-saving performance of the proposed HERO model is evaluated by simulations with different traffic patterns. The simulation results have shown that HERO can reduce the power consumption of data center networks effectively with reduced complexity. Last, several heterogeneity aware dominant resource assistant heuristic algorithms, namely, dominant residual resource aware first-fit decreasing (DRR-FFD), individual DRR-FFD (iDRR-FFD) and dominant residual resource based bin fill (DRR-BinFill), are proposed for virtual machine (VM) consolidation. The proposed heuristic algorithms exploit the heterogeneity of the VMs' requirements for different resources by capturing the differences among VMs' demands, and the heterogeneity of the physical machines' resource capacities by capturing the differences among physical machines' resources. The performance of the proposed heuristic algorithms is evaluated with different classes of synthetic workloads under different VM requirement heterogeneity conditions, and the simulation results demonstrate that the proposed heuristics achieve quite similar consolidation performance as dimension-aware heuristics with almost the same computational cost as those of the single dimensional heuristics.
Virtual Machine Consolidation In Cloud Data Centres Using A Parameter Based Placement Strategy
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Author : Abdelkhalik Mosa
language : en
Publisher:
Release Date : 2019
Virtual Machine Consolidation In Cloud Data Centres Using A Parameter Based Placement Strategy written by Abdelkhalik Mosa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
The Maltreatment Of The School Aged Child
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Author : Richard Volpe
language : en
Publisher:
Release Date : 1980-01-01
The Maltreatment Of The School Aged Child written by Richard Volpe and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980-01-01 with Child abuse categories.