• Title/Summary/Keyword: Virtual Machine (VM)

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A Development of Adaptive VM Migration Techniques in Cloud Computing (클라우드 컴퓨팅에서 적응적 VM 마이그레이션 기법 개발)

  • Lee, HwaMin
    • KIPS Transactions on Computer and Communication Systems
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    • v.4 no.9
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    • pp.315-320
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    • 2015
  • In cloud computing, server virtualization supports one or more virtual machines loaded on multiple operating systems on a single physical host server. Migration of a VM is moving the VM running on a source host to another physical machine called target host. A VM live migration is essential to support task performance optimization, energy efficiency and energy saving, fault tolerance and load balancing. In this paper, we propose open source based adaptive VM live migration technique. For this, we design VM monitoring module to decide VM live migration and open source based full-virtualization hypervisor.

Pattern Matching Optimizer for Virtual Machine Codes (가상 기계 코드를 위한 패턴 매칭 최적화기)

  • Yi Chang-Hwan;Oh Se-Man
    • Journal of Korea Multimedia Society
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    • v.9 no.9
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    • pp.1247-1256
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    • 2006
  • VM(Virtual Machine) can be considered as a software processor which interprets the abstract machine code. Also, it is considered as a conceptional computer that consists of logical system configuration. But, the execution speed of VM system is much slower than that of a real processor system. So, it is very important to optimize the code for virtual machine to enhance the execution time. In this paper, we designed and implemented the optimizer for the virtual(or abstract) machine code(VMC) which is actually SIL(Standard Intermediate Language) that is an intermediate code of EVM(Embedded Virtual Machine). The optimizer uses the pattern matching optimization techniques reflecting the characteristics of the VMC as well as adopting the existing optimization methodology. Also, we tried a benchmark test for the VMC optimizer and obtained reasonable results.

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A Study on the Improvement of the Network Performance Measurement of Virtual Machine between Host OS and Guest OS for a Mobile Personalized Software Platform based on SaaS (SaaS 기반 이동형 개인 맞춤 소프트웨어 플랫폼을 위한 VM의 Host OS와 Guest OS의 네트워크 성능 측정 방법 개선)

  • U, Su-Jeong;On, Jin-Ho;Choi, Jung-Rhan;Choi, Wan;Lee, Moon-Kun
    • Journal of Internet Computing and Services
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    • v.10 no.2
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    • pp.85-98
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    • 2009
  • Recently, there are a number of researches and developments for the personalized software platform for mobility based on SaaS. The platform requires an optimal virtual machine in order to satisfy the operating systems of various users for the software. In addition, the platform must guarantee the mobility of the users' working environments by supporting fast and secure services between internal and external networks in the platform operating systems. In order to verify the optimal behaviors of virtual machines for the platform, the performance of the virtual machines must be measured and analyzed in various perspectives. In the previous research, unfortunately, the performance of a virtual machine were conducted in the condition that a guest operating system was installed on the virtual machine and considered as a computer, by measuring the network traffic between the guest operating system and an external client operating system. This performance measurement was not suitable for a virtual machine for the platform since a number of different software must be handled in the virtual machine. In order to overcome this limitation, this paper presents a measurement method for network performance and proposes the most optimal virtual machine by the method.

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A Classification-Based Virtual Machine Placement Algorithm in Mobile Cloud Computing

  • Tang, Yuli;Hu, Yao;Zhang, Lianming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.5
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    • pp.1998-2014
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    • 2016
  • In recent years, cloud computing services based on smart phones and other mobile terminals have been a rapid development. Cloud computing has the advantages of mass storage capacity and high-speed computing power, and it can meet the needs of different types of users, and under the background, mobile cloud computing (MCC) is now booming. In this paper, we have put forward a new classification-based virtual machine placement (CBVMP) algorithm for MCC, and it aims at improving the efficiency of virtual machine (VM) allocation and the disequilibrium utilization of underlying physical resources in large cloud data center. By simulation experiments based on CloudSim cloud platform, the experimental results show that the new algorithm can improve the efficiency of the VM placement and the utilization rate of underlying physical resources.

A Tool for Analyzing VM Creation Failure caused by Virtual Disk Faults (가상 디스크 결함에 의한 가상 머신 생성 실패 진단 및 분석 도구)

  • Ku, Min-O;Min, Dug-Ki
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.9
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    • pp.127-138
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    • 2012
  • In this paper, we present a tool (named VMBootFailMonitor) to detect and analyze a failure of a VM boot creation caused by faults on virtual disks of a Xen-based VM. Also, we presents an architecture and detail analysis process of the virtual disk faults in our tool. Especially, VMBootFailMonitor provides a causual analysis result for a case of VM creation failure based on three modules which performs virtual disk analysis, virtualized system analysis and system log analysis. We also support a comparison result between boot times of normal VMs and fault detection times of VM creation based on abnormal virtual disks. At result, our tool detects VM boot failures (3~6 seconds) within normal VM boot times (8~16 seconds).

Performance Analysis to Evaluate the Suitability of MicroVM with AI Applications for Edge Computing

  • Yunha Choi;Byungchul Tak
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.3
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    • pp.107-116
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    • 2024
  • In this paper, we analyze the performance of MicroVM when running AI applications on an edge computing environment and whether it can replace current container technology and traditional virtual machines. To achieve this, we set up Docker container, Firecracker MicroVM and KVM virtual machine environments on a Raspberry Pi 4 and executed representative AI applications in each environment. We analyze the inference time, total CPU usage and trends over time and file I/O performance on each environment. The results show that there is no significant performance difference between MicroVM and container when running AI applications. Moreover, on average, a stable inference time over multiple trials was observed on MicroVM. Therefore, we can confirm that executing AI applications using MicroVM instead of container or heavy-weight virtual machine is suitable for an edge computing.

Virtual Machine Code Optimization using Profiling Data (프로파일링 데이터를 이용한 가상기계 코드 최적화)

  • Shin, Yang-Hoon;Yi, Chang-Hwan;Oh, Se-Man
    • The KIPS Transactions:PartA
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    • v.14A no.3 s.107
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    • pp.167-172
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    • 2007
  • VM(Virtual Machine) can be considered as a software processor which interprets the machine code. Also, it is considered as a conceptional computer that consists of logical system configuration. But, the execution speed of VM system is much slower than that of a real processor system. So, it is very important to optimize the code for virtual machine to enhance the execution time. Especially the optimizer for a virtual machine code on embedded devices requires the highly efficient performance to the ordinary optimizer in the respect to the optimized ratio about cost. Fundamentally, functions and basic blocks which influence the execution time of virtual machine is found, and then an optimization for them nay get the high efficiency. In this paper, we designed and implemented the optimizer for the virtual(or abstract) machine code(VMC) using profiling. Firstly, we defined the profiling information which is necessary to the optimization of VMC. The information can be obtained from dynamically executing the machine code. And we implemented VMC optimizer using the profiling information. In our implementation, the VMC is SIL(Standard Intermediate Language) that is an intermediate code of EVM(Embedded Virtual Machine). Also, we tried a benchmark test for the VMC optimizer and obtained reasonable results.

The Management and Security Plans of a Separated Virtualization Infringement Type Learning Database Using VM (Virtual Machine) (VM(Virtual Machine) 을 이용한 분리된 가상화 침해유형 학습 데이터베이스 관리와 보안방안)

  • Seo, Woo-Seok;Jun, Moon-Seog
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.8B
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    • pp.947-953
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    • 2011
  • These days, a consistent and fatal attack attribute toward a database has proportionally evolved in the similar development form to that of security policy. Because of access control-based defensive techniques regarding information created in closed networks and attacks on a limited access pathway, cases of infringement of many systems and databases based on accumulated and learned attack patterns from the past are increasing. Therefore, the paper aims to separate attack information by its types based on a virtual infringement pattern system loaded with dualistic VM in order to ensure stability to limited certification and authority to access, to propose a system that blocks infringement through the intensive management of infringement pattern concerning attack networks, and to improve the mechanism for implementing a test that defends the final database, the optimal defensive techniques, and the security policies, through research.

A Resource Reduction Scheme with Low Migration Frequency for Virtual Machines on a Cloud Cluster

  • Kim, Changhyeon;Lee, Wonjoo;Jeon, Changho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.6
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    • pp.1398-1417
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    • 2013
  • A method is proposed to reduce excess resources from a virtual machine(VM) while avoiding subsequent migrations for a computer cluster that provides cloud service. The proposed scheme cuts down on the resources of a VM based on the probability that migration may occur after a reduction. First, it finds a VM that can be scaled down by analyzing the history of the resource usage. Then, the migration probability is calculated as a function of the VM resource usage trend and the trend error. Finally, the amount of resources needed to eliminate from an underutilized VM is determined such that the migration probability after the resource reduction is less than or equal to an acceptable migration probability. The acceptable migration probability, to be set by the cloud service provider, is a criterion to assign a weight to the resource reduction either to prevent VM migrations or to enhance VM utilization. The results of simulation show that the proposed scheme lowers migration frequency by 31.6~60.8% depending on the consistency of resource demand while losing VM utilization by 9.1~21.5% compared to other known approaches, such as the static and the prediction-based methods. It is also verified that the proposed scheme extends the elapsed time before the first occurrence of migration after resource reduction 1.1~2.3-fold. In addition, changes in migration frequency and VM utilization are analyzed with varying acceptable migration probabilities and the consistency of resource demand patterns. It is expected that the analysis results can help service providers choose a right value of the acceptable migration probability under various environments having different migration costs and operational costs.

Cost-Efficient VM Placement with VM Interference Control in Cloud Environment (클라우드 환경에서 VM 간섭 제어를 고려한 비용 효율적인 VM 배치)

  • Kim, Heejae;Kim, Yusik;Youn, Chan-Hyun
    • Annual Conference of KIPS
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    • 2013.11a
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    • pp.192-194
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    • 2013
  • 가상화 기술의 발달은 클라우드 데이터센터(cloud datacenter)에서의 서버 통합(server consolidation)을 지원하며 이를 통하여 물리적 머신(physical machine, PM) 관리 비용을 감소시킬 수 있다. 그러나 서버가 통합됨에 따라 가상 머신(virtual machine, VM) 간섭이 생길 수 있고 이는 성능 감소의 원인이 된다. 따라서 VM 간섭과 PM 관리 비용을 감소시키는 것은 트레이드오프(trade-off)를 이루며 본 논문에서는 이를 해결하기 위하여 VM 간섭 계측(quantizing)을 위한 기법과 비용 효율적 VM 배치(placement)를 위한 휴리스틱(heuristics)을 제안한다.