Reactive Cloud: Consolidating Virtual Machines with Postcopy Live Migration

Hirofuchi, Takahiro; Nakada, Hidemoto; Itoh, Susumu; Sekiguchi, Satoshi

doi:10.2197/ipsjtrans.5.34

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…Sandpiper monitors server performance using a combination of black box as well as grey box techniques and uses live migration to re-arrange the physical mapping if necessary. Similar ideas are utilized in the Reactive Cloud [Hirofuchi et al 2012] system in which VMs are migrated using postcopy migration to achieve a dynamic consolidation of VMs in a datacenter as well as by Chuan, Huaxiang, Zhilou, Ying, and Lina [2012] in a study of virtual machine migration strategies.…”

Section: Related Workmentioning

confidence: 99%

Principles and Performance Characteristics of Algorithms for Live VM Migration

Svärd

Hudzia

Walsh

et al. 2015

SIGOPS Oper. Syst. Rev.

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Since first demonstrated by Clark et al. in 2005, live migration of virtual machines has both become a standard feature of hypervisors and created an active field of research. However, the rich ongoing research in live migration focus mainly on performance improvements to well-known techniques, most of them being variations of the Clark approach. In order to advance live migration beyond incremental performance improvements, it is important to gain a deeper understanding of the live migration problem itself and its underlying principles.To address this issue, this contribution takes a step back and investigates the essential characteristics of live migration. The paper identifies five fundamental properties of live migration and uses these to investigate, categorize, and compare three approaches to live migration: precopy, postcopy and hybrid. The evaluated algorithms include well-known techniques derived from that of Clark as well as novel RDMA in-kernel approaches. Our analysis of the fundamental properties of the algorithms is validated by a set of experiments. In these, we migrate virtual machines with large memory sizes hosting workloads with high page dirtying rates to expose differences and limitations of the different approaches. Finally, we provide guidelines for which approach to use in different scenarios.

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Section: Related Workmentioning

confidence: 99%

Principles and Performance Characteristics of Algorithms for Live VM Migration

Svärd

Hudzia

Walsh

et al. 2015

SIGOPS Oper. Syst. Rev.

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“…The memtouch program works as a workload that has a linear correlation between CPU utilization levels and memory update speeds. It produces the memory update speed at a given CPU utilization level, by interleaving busy loops, memory updates and micro sleeps in an appropriate ratio as explained in our previous work [14].…”

Section: Experimental Conditionsmentioning

confidence: 99%

SimGrid VM: Virtual Machine Support for a Simulation Framework of Distributed Systems

Hirofuchi

Lèbre

Pouilloux

2018

IEEE Trans. Cloud Comput.

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International audienceAs real systems become larger and more complex, the use of simulator frameworks grows in our research community. By leveraging them, users can focus on the major aspects of their algorithm, run in-siclo experiments (i.e., simulations), and thoroughly analyze results, even for a large-scale environment without facing the complexity of conducting in-vivo studies (i.e., on real testbeds). Since nowadays the virtual machine (VM) technology has become a fundamental building block of distributed computing environments, in particular in cloud infrastructures, our community needs a full-fledged simulation framework that enables us to investigate large-scale virtualized environments through accurate simulations. To be adopted, such a framework should provide easy-to-use APIs as well as accurate simulation results. In this paper, we present a highly-scalable and versatile simulation framework supporting VM environments. By leveraging SimGrid, a widely-used open-source simulation toolkit, our simulation framework allows users to launch hundreds of thousands of VMs on their simulation programs and control VMs in the same manner as in the real world (e.g., suspend/resume and migrate). Users can execute computation and communication tasks on physical machines (PMs) and VMs through the same SimGrid API, which will provide a seamless migration path to IaaS simulations for hundreds of SimGrid users. Moreover, SimGrid VM includes a live migration model implementing the precopy migration algorithm. This model correctly calculates the migration time as well as the migration traffic, taking account of resource contention caused by other computations and data exchanges within the whole system. This allows user to obtain accurate results of dynamic virtualized systems. We confirmed accuracy of both the VM and the live migration models by conducting several micro-benchmarks under various conditions. Finally, we conclude the article by presenting a first use-case of one consolidation algorithm dealing with a significant number of VMs/PMs. In addition to confirming the accuracy and scalability of our framework, this first scenario illustrates the main interest of SimGrid VM: investigating through in-siclo experiments pros/cons of new algorithms in order to limit expensive in-vivo experiments only to the most promising ones

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“…Post-copy reduces the migration time for memory-write-intensive applications and usually has smaller downtime than pre-copy. Reactive cloud [13] uses post-copy to react to sudden overloads quickly. Scatter-Gather VM migration [6] allows fast eviction of a VM when the destination machine is resource constrained.…”

Section: Related Workmentioning

confidence: 99%

Quick eviction of virtual machines through proactive live snapshots

Fernando

Bagdi

Yao-hui

et al. 2016

Proceedings of the 9th International Conference on Utility and Cloud Computing

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Cloud computing platforms routinely use virtualization to improve service availability, resiliency, and flexibility. Live migration of Virtual Machines (VM) is a key technique to quickly migrate workloads in response to events such as impending failure or load changes. Despite extensive research, state-of-the-art live migration approaches take a long time to migrate a VM (in the order of tens of seconds for moderately sized VMs) which in turn negatively impacts the application performance during migration. We present Quick Eviction, a new approach to significantly speed up the eviction of a VM from the source host with low impact on VM's performance during migration. Our approach can also improve the effectiveness of VM resilience tools that back up a VM's state in anticipation of system failures. The insight behind Quick Eviction is that the majority of time to evict a VM during migration is due to the transfer of memory contents over the network, sometimes repeatedly. Before migration, Quick Eviction regularly snapshots the VM's memory to a destination or a failover node. During the actual migration, Quick Eviction has to transfer only a small amount of dirtied memory resulting in a very short time to completely evict the VM out of the source. The key challenge is to dynamically adapt the snapshot intervals so as to have minimal impact on application performance during migration. We show that our implementation of Quick Eviction in the *

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Reactive Cloud: Consolidating Virtual Machines with Postcopy Live Migration

Cited by 5 publications

References 10 publications

Principles and Performance Characteristics of Algorithms for Live VM Migration

Principles and Performance Characteristics of Algorithms for Live VM Migration

SimGrid VM: Virtual Machine Support for a Simulation Framework of Distributed Systems

Quick eviction of virtual machines through proactive live snapshots

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