Live virtual machine migration based on improved pre-copy approach

Ma, Fei; Liu, Feng; Liu, Zhen

doi:10.1109/icsess.2010.5552416

Cited by 71 publications

(25 citation statements)

References 6 publications

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“…The study indicated that our approach saves the total migration time by at least 65% and at most 75% in the memory intensive environment. This is in contrast to previous work in which, in the memory intensive environment, migration takes a long time or reaches a deadlock [6], [8]- [10]. In same environment, our approach can reduce more the total migration time compared to MECOM as much as 40%.…”

Section: Resultscontrasting

confidence: 48%

Optimized Pre-copy Migration Using STORD for Memory Intensive Environment

Cha¹,

Shin²,

Kim³

2015

IJCEE

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Abstract:The conventional pre-copy method for live migration leads to redundant transmission of data transmitted. In addition, the migration efficiency decreases in the memory intensive environment where the memory is frequently modified because the modified memory data should do retransmission. Recently, these problems intensified because of growing complexity of computing environment such as Big-data and Cloud. In order to address these problems, we propose a method that is split transfer and omitting redundant dirty pages (STORD). We compared our approach with the conventional pre-copy method to evaluate the performance. In particular, we used a static bandwidth and generated a same size of dirty pages on split memory data for migration to show the effect of transferring the split memory. Simulation result showed that the proposed method saved the total migration time from 6% to 65% compared to pre-copy method. Also, when the environment has dirty page rate of 90%, our approach took less total migration time than MECOM which is the improvised method of pre-copy. Therefore, the proposed method is able to alleviate system performance degradation because our approach takes less migration time than previous method in Big-data or the multi-core environment.

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Section: Resultscontrasting

confidence: 48%

Optimized Pre-copy Migration Using STORD for Memory Intensive Environment

Cha¹,

Shin²,

Kim³

2015

IJCEE

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“…Live migration has two phases: In the first phase, the RAM content and the state of the virtual machine are iteratively copied to the target server while the VM executes in the source server. In the second phase, the VM is stopped briefly to prevent further memory updates, the latest updates are copied to the target server, and the VM is started in the target server [17], [18]. These phases require computation and communication resources and introduce VM down-time (phase two).…”

Section: ) Migration Timementioning

confidence: 99%

Mutual Influence of Application- and Platform-Level Adaptations on Energy-Efficient Computing

Rybina

Dargie

Schöne

et al. 2015

2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing

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Abstract-We experimentally investigate the mutual influence of application-and platform-level adaptations in a virtualized cluster environment. At the application level, applications can adapt to a changing execution environment by dynamically exchanging components that enable them to trade energy for utility and vice versa. Likewise, at the platform level, virtual machine monitors can migrate virtual machines from one server to another either to consolidate workloads and switch-off underutilized servers or to distribute the workload of overloaded servers. Our experiment quantify impacts of various types of adaptations on QoS, power consumption, and energy-overhead.

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“…클라우드 컴퓨팅 환경에서 해당 부하를 동적으로 재배 치시키는 이주 기법은 스토리지 복제와 가상머신의 이주 의 순서에 따라 선 복제 모델(pre-copy) [5] 과 후 복제(postcopy) [5] …”

Section: Storage Copy Schemeunclassified

Fuzzy logic-based Priority Live Migration Model for Efficiency

Park¹,

Jaekwon²,

Choi³

et al. 2015

Journal of the Korea Society for Simulation

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If the cloud computing environment is not sufficiently provide the required resources due to the number of virtual server to process the request, may cause a problem that the load applied to the specific server. Migration administrator receive the resources of each physical server for improving the efficiency of the virtual server that exists in the physical servers, and determines the migration destination based on the simulation results. But, there is more overhead predicting the future resource consumption of all the physical server to decide the migration destination through the simulation process in large and complex cloud computing environments. To solve this problem, we propose an improved prediction method with the simulation-based approach. The proposed method is a fuzzy-logic based priority model for VM migration. We design a proposed model with the DEVS formalism. And we also measure and compare a performance and migration count with existing simulation-based migration method. FPLM shows high utilization.

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Live virtual machine migration based on improved pre-copy approach

Cited by 71 publications

References 6 publications

Optimized Pre-copy Migration Using STORD for Memory Intensive Environment

Optimized Pre-copy Migration Using STORD for Memory Intensive Environment

Mutual Influence of Application- and Platform-Level Adaptations on Energy-Efficient Computing

Fuzzy logic-based Priority Live Migration Model for Efficiency

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