The Experts below are selected from a list of 29589 Experts worldwide ranked by ideXlab platform
Anja Strunk - One of the best experts on this subject based on the ideXlab platform.
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a lightweight model for estimating energy cost of Live Migration of virtual machines
International Conference on Cloud Computing, 2013Co-Authors: Anja StrunkAbstract:Live Migration, the process of moving a virtual machine (VM) interruption-free between physical hosts is a core concept in modern data centers. Power management strategies use Live Migration to consolidate services in a cluster environment and switch off underutilized machines to save power. However, most Migration models do not consider the energy cost of Migration. In a previous study we showed that Live Migration entails an energy overhead and the size of this overhead varies with the RAM size of the virtual machine and the available network bandwidth. This paper extends our previous work and proposes a lightweight mathematical model to estimate the energy cost of Live Migration of an idle virtual machine quantitatively. A series of experiments were conducted on KVM to profile the Migration time and the power consumption during Live Migration. Based on these data we derived an energy cost model that predicts the energy overhead of Live Migration of virtual machines with an accuracy of higher than 90%.
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does Live Migration of virtual machines cost energy
Advanced Information Networking and Applications, 2013Co-Authors: Anja Strunk, Waltenegus DargieAbstract:Live Migration, the process of moving a virtual machine (VM) interruption-free between physical hosts is a core concept in modern data centers. Power management strategies use Live Migration to consolidate services in a cluster environment and to switch off underutilized machines to save power. However, most Migration models do not consider the energy cost of Migration. This paper experimentally investigates the factors that affect the power consumption and the duration of virtual machine Migration. We use the KVM platform for our experiment and show that a Live Migration entails an energy overhead and the size of this overhead varies with the size of the virtual machine and the available network bandwidth.
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AINA - Does Live Migration of Virtual Machines Cost Energy
2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), 2013Co-Authors: Anja Strunk, Waltenegus DargieAbstract:Live Migration, the process of moving a virtual machine (VM) interruption-free between physical hosts is a core concept in modern data centers. Power management strategies use Live Migration to consolidate services in a cluster environment and to switch off underutilized machines to save power. However, most Migration models do not consider the energy cost of Migration. This paper experimentally investigates the factors that affect the power consumption and the duration of virtual machine Migration. We use the KVM platform for our experiment and show that a Live Migration entails an energy overhead and the size of this overhead varies with the size of the virtual machine and the available network bandwidth.
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IEEE CLOUD - A Lightweight Model for Estimating Energy Cost of Live Migration of Virtual Machines
2013 IEEE Sixth International Conference on Cloud Computing, 2013Co-Authors: Anja StrunkAbstract:Live Migration, the process of moving a virtual machine (VM) interruption-free between physical hosts is a core concept in modern data centers. Power management strategies use Live Migration to consolidate services in a cluster environment and switch off underutilized machines to save power. However, most Migration models do not consider the energy cost of Migration. In a previous study we showed that Live Migration entails an energy overhead and the size of this overhead varies with the RAM size of the virtual machine and the available network bandwidth. This paper extends our previous work and proposes a lightweight mathematical model to estimate the energy cost of Live Migration of an idle virtual machine quantitatively. A series of experiments were conducted on KVM to profile the Migration time and the power consumption during Live Migration. Based on these data we derived an energy cost model that predicts the energy overhead of Live Migration of virtual machines with an accuracy of higher than 90%.
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costs of virtual machine Live Migration a survey
World Congress on Services, 2012Co-Authors: Anja StrunkAbstract:Live Migration allows moving a continuously running VM from one physical host to another. It provides special benefit for data centers in a variety of scenarios including load balancing, maintenance and power management. However virtual machine Live Migration leads to performance loss and energy overhead that cannot be ignored in modern data centers, especially if critical business goals are to be met. In this paper we summarize, classify and evaluate current approaches with respect to determine costs of virtual machine Live Migration.
Ping Yang - One of the best experts on this subject based on the ideXlab platform.
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INFOCOM - Live Migration Ate My VM: Recovering a Virtual Machine after Failure of Post-Copy Live Migration
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Co-Authors: Dinuni Fernando, Kartik Gopalan, Jonathan Terner, Ping YangAbstract:Post-copy is one of the two key techniques (besides pre-copy) for Live Migration of virtual machines in data centers. Post-copy provides deterministic total Migration time and low downtime for write-intensive VMs. However, if post-copy Migration fails for any reason, the migrating VM is lost because the VM’s latest consistent state is split between the source and destination nodes during Migration. In this paper, we present PostCopyFT, a new approach to recover a VM after a destination or network failure during post-copy Live Migration using an efficient reverse incremental checkpointing mechanism. We have implemented and evaluated our approach in the KVM/QEMU platform. Our experimental results show that the total Migration time of post-copy remains unchanged while maintaining low failover time, downtime, and application performance overhead.
Kartik Gopalan - One of the best experts on this subject based on the ideXlab platform.
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INFOCOM - Live Migration Ate My VM: Recovering a Virtual Machine after Failure of Post-Copy Live Migration
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Co-Authors: Dinuni Fernando, Kartik Gopalan, Jonathan Terner, Ping YangAbstract:Post-copy is one of the two key techniques (besides pre-copy) for Live Migration of virtual machines in data centers. Post-copy provides deterministic total Migration time and low downtime for write-intensive VMs. However, if post-copy Migration fails for any reason, the migrating VM is lost because the VM’s latest consistent state is split between the source and destination nodes during Migration. In this paper, we present PostCopyFT, a new approach to recover a VM after a destination or network failure during post-copy Live Migration using an efficient reverse incremental checkpointing mechanism. We have implemented and evaluated our approach in the KVM/QEMU platform. Our experimental results show that the total Migration time of post-copy remains unchanged while maintaining low failover time, downtime, and application performance overhead.
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Scatter-Gather Live Migration of Virtual Machines
IEEE Transactions on Cloud Computing, 2018Co-Authors: Umesh Deshpande, Danny Chan, Kartik Gopalan, Steven Chan, Nilton BilaAbstract:We introduce a new metric for Live Migration of virtual machines (VM) called eviction time defined as the time to evict the state of one or more VMs from the source host. Eviction time determines how quickly the source can be taken offline or its resources repurposed for other VMs. In traditional Live Migration, such as pre-copy and post-copy, eviction time equals the total Migration time because the source is tied up until the destination receives the entire VM. We present Scatter-Gather Live Migration which decouples the source and destination during Migration to reduce eviction time when the destination is slow. The source scatters the memory of VMs to multiple nodes, including the destination and one or more intermediaries. Concurrently, the destination gathers the VMs’ memory from the intermediaries and the source. Thus eviction from the source is no longer bottlenecked by the reception speed of the destination. We support simultaneous Live eviction of multiple VMs and exploit deduplication to reduce network overhead. Our Scatter-Gather implementation in the KVM/QEMU platform reduces the eviction time by up to a factor of 6 against traditional pre-copy and post-copy while maintaining comparable total Migration time when the destination is slower than the source.
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IPDPS - Agile Live Migration of Virtual Machines
2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2016Co-Authors: Umesh Deshpande, Danny Chan, Ten-young Guh, James Edouard, Kartik Gopalan, Nilton BilaAbstract:A key attraction of virtual machines (VMs) is Live Migration - the ability to move their execution state across physical machines even as the VMs continue to run. Unfortunately, the traditional pre-copy and post-copy techniques are not agile in the face of resource pressures at the source host, since it takes a long time to transfer the memory state of a VM. Consequently, the performance suffers for all VMs - those being migrated as well as those being left behind. Prior works have attempted to optimize indirect measures of Migration effectiveness such as downtime, total Migration time, and network overhead. However, none have treated the performance of VMs impacted by Migration as the primary metric of Migration effectiveness. We propose an Agile Live Migration technique that quickly recovers the performance of all VMs under resource pressure by eliminating resource pressure faster than traditional Live Migration. The working set of a VM is typically much smaller than its full memory footprint. Our approach works by transparently tracking the working set of each VM and offloading the non-working set (cold pages) in advance to portable per-VM swap devices. We present a new hybrid pre/post-copy technique that reduces the performance impact on the VM's workload by transferring only the working set of the VM while enabling destination to remotely access cold pages from the per-VM swap device. We describe the challenges in the design and implementation of Agile Live Migration in the KVM/QEMU platform without modifying the guest OS in the VM. When Live migrating under memory pressure, we demonstrate a reduction in the performance impact on VMs by a up to factor of 2, reduction in Migration time by up to factor of 4 besides reduction in memory pressure on both the source and destination hosts.
Phithak Thaenkaew - One of the best experts on this subject based on the ideXlab platform.
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SNPD - Performance comparisons and data compression of time-bound Live Migration and pre-copy Live Migration of virtual machines
2017 18th IEEE ACIS International Conference on Software Engineering Artificial Intelligence Networking and Parallel Distributed Computing (SNPD), 2017Co-Authors: Kasidit Chanchio, Phithak ThaenkaewAbstract:Pre-copy Live Migration is a popular virtual machine (VM) Live Migration mechanism that has been used in most hypervisors. In this mechanism, a key parameter, namely the maximum tolerable downtime, is required for each Migration. However, defining an appropriate value for this parameter is nontrivial, especially for the Migration of a virtual machine running CPU-intensive and memory-intensive applications. If an inappropriate value is used, the Migration may suffer poor performance. Time-bound Live Migration (TLM) is another Live Migration mechanism that was proposed to solve this problem. The TLM can operate automatically without the need for the maximum tolerable downtime. Thus, the operational burden and performance penalty due to the configuration of the maximum tolerable downtime are eliminated. The contributions of this study are two folds. First, a novel compression framework for TLM, namely TLMZ, is proposed. Second, the Live Migration performances of TLM and TLMZ are evaluated against those of the pre-copy mechanism. In our comparisons, the pre-copy mechanism was configured to operate using a range of maximum tolerable downtime values and a number of compression options. An extensive number of experiments have been conducted. In our experiments, the TLM, TLMZ, and pre-copy mechanisms are used to migrate VMs running four OpenMP NAS parallel benchmarks. Experimental results show that TLM and TLMZ are practical solutions for the Migrations of VMs running CPU-intensive and memory-intensive applications.
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CCGRID - Time-Bound, Thread-Based Live Migration of Virtual Machines
2014 14th IEEE ACM International Symposium on Cluster Cloud and Grid Computing, 2014Co-Authors: Kasidit Chanchio, Phithak ThaenkaewAbstract:Live Migration of virtual machines is the ability to move running virtual machines between two computers with minimal downtime. Although various Migration mechanisms such as pre-copy, post-copy, and state compression have been proposed, they may suffer long Migration times when the migrating virtual machines run large computation and memory intensive workloads. This paper presents the design and implementation of a novel Time-bound, thread-based Live Migration (TLM) mechanism, where additional threads are added to the pre-copy Live Migration algorithm to handle virtual machine state transfers within a bounded time period. In the time-bound principle, the upper-bound Migration time of a virtual machine is proportional to the size of the virtual machine's memory. We propose a CPU over-committing mechanism to minimize Migration downtime and avoid performance impacts to other virtual machines when the Migration threads are in operation. We have implemented a prototype implementation of TLM on KVM, and conducted experiments by migrating virtual machines running a number of Class D OpenMP and MPI NAS parallel benchmarks. Experimental results showed the following: (i) TLM finished Live Migration in a bounded time period. Users are able to measure progress of Migration operation. (ii) The CPU over-committing mechanism can be used to minimize Live Migration downtime. However, communication performance of virtual machines during Live Migration also declined as the number of over-committed CPUs reduced. The patterns of decline depended on execution behaviors of the applications on the virtual machines. (iii) The execution time increases of the OpenMP and MPI versions of the MG and IS benchmarks in our experiments were approximately equal to the Migration times of TLM. (iv) We evaluated our CPU over-committing mechanism against the auto-convergence mechanism recently developed in kvm-1.6. We found that both mechanisms have their pros and cons, and their performance results are varied with application. Based on these results, we believe that the TLM design is practical for Live Migration of virtual machines running memory-intensive workloads, and the time-bound principle is an important new feature for pre-copy Live Migration optimization.
Christoph Meinel - One of the best experts on this subject based on the ideXlab platform.
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CLOSER - Machine Learning Approach for Live Migration Cost Prediction in VMware Environments
Proceedings of the 9th International Conference on Cloud Computing and Services Science, 2019Co-Authors: Mohamed Esam Elsaid, Hazem M Abbas, Christoph MeinelAbstract:Virtualization became a commonly used technology in datacenters during the last decade. Live Migration is an essential feature in most of the clusters hypervisors. Live Migration process has a cost that includes the Migration time, downtime, IP network overhead, CPU overhead and power consumption. This Migration cost cannot be ignored, however datacenter admins do Live Migration without expectations about the resultant cost. Several research papers have discussed this problem, however they could not provide a practical model that can be easily implemented for cost prediction in VMware environments. In this paper, we propose a machine learning approach for Live Migration cost prediction in VMware environments. The proposed approach is implemented as a VMware PowerCLI script that can be easily implemented and run in any vCenter Server Cluster to do data collection of previous Migrations statistics, train the machine learning models and then predict Live Migration cost. Testing results show how the proposed framework can predict Live Migration time, network throughput and power consumption cost with accurate results and for different kinds of workloads. This helps datacenters admins to have better planning for their VMware environments Live Migrations.
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machine learning approach for Live Migration cost prediction in vmware environments
International Conference on Cloud Computing and Services Science, 2019Co-Authors: Mohamed Esam Elsaid, Hazem M Abbas, Christoph MeinelAbstract:Virtualization became a commonly used technology in datacenters during the last decade. Live Migration is an essential feature in most of the clusters hypervisors. Live Migration process has a cost that includes the Migration time, downtime, IP network overhead, CPU overhead and power consumption. This Migration cost cannot be ignored, however datacenter admins do Live Migration without expectations about the resultant cost. Several research papers have discussed this problem, however they could not provide a practical model that can be easily implemented for cost prediction in VMware environments. In this paper, we propose a machine learning approach for Live Migration cost prediction in VMware environments. The proposed approach is implemented as a VMware PowerCLI script that can be easily implemented and run in any vCenter Server Cluster to do data collection of previous Migrations statistics, train the machine learning models and then predict Live Migration cost. Testing results show how the proposed framework can predict Live Migration time, network throughput and power consumption cost with accurate results and for different kinds of workloads. This helps datacenters admins to have better planning for their VMware environments Live Migrations.
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SC² - Enhanced Cost Analysis of Multiple Virtual Machines Live Migration in VMware Environments
2018 IEEE 8th International Symposium on Cloud and Service Computing (SC2), 2018Co-Authors: Mohamed Esam Elsaid, Ahmed Shawish, Christoph MeinelAbstract:Live Migration is an important feature in modern software-defined datacenters and cloud computing environments. Dynamic resource management, load balance, power saving and fault tolerance are all dependent on the Live Migration feature. Despite the importance of Live Migration, the cost of Live Migration cannot be ignored and may result in service availability degradation. Live Migration cost includes the Migration time, downtime, CPU overhead, network and power consumption. There are many research articles that discuss the problem of Live Migration cost with different scopes like analyzing the cost and relate it to the parameters that control it, proposing new Migration algorithms that minimize the cost and also predicting the Migration cost. For the best of our knowledge, most of the papers that discuss the Migration cost problem focus on open source hypervisors. For the research articles focus on VMware environments, none of the published articles proposed Migration time, network overhead and power consumption modeling for single and multiple VMs Live Migration. In this paper, we propose empirical models for the Live Migration time, network overhead and power consumption for single and multiple VMs Migration. The proposed models are obtained using a VMware based testbed.
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IC2E - Multiple Virtual Machines Live Migration Performance Modelling -- VMware vMotion Based Study
2016 IEEE International Conference on Cloud Engineering (IC2E), 2016Co-Authors: Mohamed Esam Elsaid, Christoph MeinelAbstract:Live Migration is one of the powerful features in virtual datacenters environment. Servers load balance, power saving and dynamic resource management techniques are all dependent on Live Migration feature in virtual datacenters. So it is important to study virtual machine Live Migration processes and analyze its performance impact on datacentres resources. In this research, the performance analysis for single and multiple virtual machines Migration has led to getting empirical models that can be used for Live Migration overhead estimation and providing resource management techniques that are Migration overhead aware.
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FiCloud - Live Migration Impact on Virtual Datacenter Performance: Vmware vMotion Based Study
2014 International Conference on Future Internet of Things and Cloud, 2014Co-Authors: Mohamed Esam Elsaid, Christoph MeinelAbstract:Cloud computing is the future wave of information technology that provides infrastructure, platform and application as on demand services with low cost and rapid scalability. Infrastructure resources virtualization is the backbone of cloud computing to meet on demand, rapid scalability and resource pooling as the main cloud computing characteristics. Live Migration is one of the powerful features in datacenters virtualization. Hosts load balance, power saving, failure recovery and dynamic resource allocation are all dependent on having Live Migration for the virtual machines. So studying and modeling Live Migrations is important to predict its impact on the datacenter performance and to take the Migration decision at the optimum times. In this paper, we study the impact of Live Migration on the datacenter resources network and power consumption for VMware environment. This overhead modeling can be used to estimate the Live Migration impact on datacenter resources utilization given the virtual machine and network characteristics. Based on this estimation, the network admin can be alerted with this estimated overhead in order to confirm the Live Migration request or to postpone it to another optimum time for minimum interruption on the running applications.