A live storage migration mechanism over wan and its performance evaluation

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

doi:10.1145/1555336.1555348

Cited by 37 publications

(20 citation statements)

References 6 publications

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“…Using network attached storage (NAS), downtime can be brought down to the order of milliseconds (Mian et al, 2011) but for a local persistent storage the downtime will be significantly higher. Migrating CPU state, migrating memory content (Ibrahim et al, 2011), migrating storage content (Hirofuchi et al, 2009a(Hirofuchi et al, , 2009b, and migrating network connections are the important steps to be followed in migrating a VM from source host do destination host. Clark et al (2011) proposed pre-copy migration technique.…”

Section: Literature Surveymentioning

confidence: 99%

Live migration of virtual machines with their local persistent storage in a data intensive cloud

Modi

Achar

Thilagam

2017

IJHPCN

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Abstract:Processing large volumes of data to drive their core business has been the primary objective of many firms and scientific applications in these days. Cloud computing being a large-scale distributed computing paradigm can be used to cater for the needs of data intensive applications. There are various approaches for managing the workload on a data intensive cloud. Live migration of a virtual machine is the most prominent paradigm. Existing approaches to live migration use network attached storage where just the run time state needs to be transferred. Live migration of virtual machines with local persistent storage has been shown to have performance advantages like security, availability and privacy. This paper presents an optimised approach for migration of a virtual machine along with its local storage by considering the locality of storage access. Count map combined with a restricted block transfer mechanism is used to minimise the downtime and overhead. The solution proposed is tested by various parameters like bandwidth, write access patterns and threshold. Results show the improvement in downtime and reduction in overhead.

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Section: Literature Surveymentioning

confidence: 99%

Live migration of virtual machines with their local persistent storage in a data intensive cloud

Modi

Achar

Thilagam

2017

IJHPCN

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“…The proposed mechanism builds on a postcopy migration technique that we previously developed [5] and works as follows: first, a virtual machine monitor (VMM) performs a regular VM migration, which does not include the relocation of storage. Then, the destination storage server starts processing disk I/O requests from the migrated VM.…”

Section: Proposed Mechanismmentioning

confidence: 99%

“…By transferring the data in advance, the proposed mechanism can dramatically reduce the amount of data transferred and consequently the time required to complete the live migration of the whole VM state. The live storage migration is implemented by using a postcopy migration technique [5]. The amount of data transferred for storage migration is de- terministic and does not change depending on the activity of the VM.…”

Section: Introductionmentioning

confidence: 99%

A WAN-Optimized Live Storage Migration Mechanism toward Virtual Machine Evacuation upon Severe Disasters

Hirofuchi¹,

Tsugawa

Nakada³

et al. 2013

IEICE Trans. Inf. & Syst.

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SUMMARYWide-area VM migration is a technology with potential to aid IT services recovery since it can be used to evacuate virtualized servers to safe locations upon a critical disaster. However, the amount of data involved in a wide-area VM migration is substantially larger compared to VM migrations within LAN due to the need to transfer virtualized storage in addition to memory and CPU states. This increase of data makes it challenging to relocate VMs under a limited time window with electrical power. In this paper, we propose a mechanism to improve live storage migration across WAN. The key idea is to reduce the amount of data to be transferred by proactively caching virtual disk blocks to a backup site during regular VM operation. As a result of pre-cached disk blocks, the proposed mechanism can dramatically reduce the amount of data and consequently the time required to live migrate the entire VM state. The mechanism was evaluated using a prototype implementation under different workloads and network conditions, and we confirmed that it dramatically reduces the time to complete a VM live migration. By using the proposed mechanism, it is possible to relocate a VM from Japan to the United States in just under 40 seconds. This relocation would otherwise take over 1500 seconds, demonstrating that the proposed mechanism was able to reduce the migration time by 97.5%.

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“…In the post-copy model [15,16] depicted in Figure 2.1, storage migration is executed after memory migration completes and the VM is running at the destination. Two mechanisms are used to copy disk blocks over: background copying and on-demand fetching.…”

Section: Pre-copy Model Without Schedulingmentioning

confidence: 99%

Workload-aware live storage migration for clouds

Zheng

Sripanidkulchai

2011

SIGPLAN Not.

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The emerging open cloud computing model will provide users with great freedom to dynamically migrate virtualized computing services to, from, and between clouds over the wide-area. While this freedom leads to many potential benefits, the running services must be minimally disrupted by the migration. Unfortunately, current solutions for wide-area migration incur too much disruption as they will significantly slow down storage I/O operations during migration. The resulting increase in service latency could be very costly to a business. This paper presents a novel storage migration scheduling algorithm that can greatly improve storage I/O performance during wide-area migration. Our algorithm is unique in that it considers individual virtual machine's storage I/O workload such as temporal locality, spatial locality and popularity characteristics to compute an efficient data transfer schedule. Using a fully implemented system on KVM and a trace-driven framework, we show that our algorithm provides large performance benefits across a wide range of popular virtual machine workloads.

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A live storage migration mechanism over wan and its performance evaluation

Cited by 37 publications

References 6 publications

Live migration of virtual machines with their local persistent storage in a data intensive cloud

Live migration of virtual machines with their local persistent storage in a data intensive cloud

A WAN-Optimized Live Storage Migration Mechanism toward Virtual Machine Evacuation upon Severe Disasters

Workload-aware live storage migration for clouds

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