• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2012년도 추계학술발표대회
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• pp.204-206
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• 2012

SMP(Symmetric Multi-Processing)는 Shared memory bus 를 사용함으로써 scalability 가 제한적이었다. 이런 SMP의 scalability 제한을 극복하기 위해 제안 된 것이 NUMA(Non Uniform Memory Access)이다. NUMA는 memory bus 를 CPU 별 local 하게 가지고 있어 자신이 가지는 memory 영역에 대해서는 다른 영역을 접근하는 것 보다 더 빠른 latency 를 가지는 구조이다. Local 한 memory 영역의 존재는 scalability를 높여 주었지만 서버 가상화 환경에서 VM을 동적으로 scheduling 을 하였을 때 VM의 page 가 실행되는 core 의 local 한 메모리 영역에 존재하지 않게 되면 remote access로 인해 local access보다 성능이 떨어진다. 이 논문에서는 서버 가상화 환경에서 최신 architecture인 AMD bulldozer에서 NUMA affinity가 위반되었을 때 발생하는 성능 저하와 어떤 상황에서 이런 NUMA affinity가 위반되어도 성능저하가 없는지 연구하였다.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제23권4호
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• pp.199-209
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• 2017

최근 실시간 임베디드 시스템 분야에서 가상화를 이용한 시스템 통합에 대한 관심이 꾸준히 증가하고 있다. 가상화 기술은 하이퍼바이저의 개입으로 인한 오버헤드를 수반하며 이는 가상 머신 상에서 구동되는 프로그램의 수행시간을 증가시킨다. 수행시간이 증가함에 따라 가상 머신 상에 있는 소프트웨어의 성능이 하락하며, 실시간성을 유지하기 어려워진다. 본 논문에서는 이러한 문제를 해결하기 위해 가상머신 상의 프로그램이 하이퍼바이저의 개입 없이 직접 물리적인 자원에 접근할 수 있도록 하이퍼바이저를 설계하고 구현하였으며 이를 K-Hypervisor라 부른다. 실험 결과에 따르면 K-Hypervisor 상에서 구동되는 프로그램들의 수행시간은 네이티브 환경에서 측정된 결과와 비교하여 평균적으로 약 3% 정도 증가한다. 또한 성능 저하가 태스크가 접근하는 자원의 종류나 빈도와 관계없이 항상 일정하여 소프트웨어의 실시간성을 유지하기에 적합하다.

• 한국정보과학회논문지:시스템및이론
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• 제35권12호
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• pp.568-575
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• 2008

서버 가상화 기술에 의한 서버 통합은 효율적인 자원 사용에 따른 비용적인 장점이 있다. 그러나 하나의 물리적 장치에 여러 개의 서버가 가상머신으로 함께 동작함으로써 더욱 복잡한 부하특성을 가지게 되었다. 따라서 이를 해결하기 위한 효율적인 자원관리 방법이 요구된다. 이러한 문제에 대한 해결방법으로 제안된 것이 가상머신 이동(live migration)[1,2]을 이용한 가상머신 동적 재배치 기법이다[3,4]. 본 논문은 가상머신 동적 재배치 알고리즘에 있어서 각 자원요소(CPU, network I/O, memory)들의 활용률을 다차원 공간상에서 분석하여 조율함으로써 서버통합의 자원 효율성을 증가시키는 방법(Server consolidation optimizing algorithm)을 제안하고 있다. 실험을 위해서 여러 대의 통합서버와 수많은 서비스를 생성하여야 하는 어려움이 있기 때문에 본 논문에서는 기업환경에서의 서버 가상화 프로젝트 경험을 바탕으로 서버의 부하변화와 유사한 패턴의 모니터링 데이타들을 정의하여 수치적인 시뮬레이션을 통해 sandpiper[3]와 SCOA 알고리즘의 부하 균형에 대한 효율성을 비교하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• International Journal of Computer Science & Network Security
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• 제21권11호
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• 대한임베디드공학회논문지
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• 제10권4호
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• pp.233-239
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• 2015

This paper describes a method that is integrated trace for real-time virtualization environment. This method has solved the problem that the performance trace may not be able to analyze integrated method between heterogeneous operating systems which is consists of real-time operating systems and general-purpose operating system. In order to solve this problem, we have attempted to reuse the performance analysis function in general-purpose operating system, thereby real-time operating systems can be analyzed along with general-operating system. Furthermore, we have implemented a prototype based on ARM Cortex-A15 dual-core processor. By using this integrated trace method, real-time system developers can be improved productivity and reliability of results on real-time virtualization environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5234-5251
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• 2018

It is well-known that virtualization technology can bring many benefits not only to users but also to service providers. From the view of system security and resource utility, higher resource sharing degree and higher system reliability can be obtained by the introduction of virtualization technology in distributed cloud. The small size time-sharing multiplexing technology which is based on virtual machine in distributed cloud platform can enhance the resource utilization effectively by server consolidation. In this paper, the concept of memory block and user satisfaction is redefined combined with user requirements. According to the unbalanced memory resource states and user preference requirements in multi-virtual machine environments, a model of proper memory resource allocation is proposed combined with memory block and user satisfaction, and at the same time a memory optimization allocation algorithm is proposed which is based on virtual memory block, makespan and user satisfaction under the premise of an orderly physical nodes states also. In the algorithm, a memory optimal problem can be transformed into a resource workload balance problem. All the virtual machine tasks are simulated in Cloudsim platform. And the experimental results show that the problem of virtual machine memory resource allocation can be solved flexibly and efficiently.

• KNOM Review
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• 제24권1호
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• pp.1-12
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• 2021

VM (Virtual Machine) live migration은 VM에서 동작하는 서비스의 downtime을 최소화하면서 해당 VM을 다른 서버 노드로 이전시키는 서버 가상화 기술이다. 클라우드 데이터센터에서는 로드밸런싱, 특정 위치 서버로의 consolidation 통한 전력 소비 감소, 서버 유지보수(maintenance) 작업 중에도 사용자에게 무중단 서비스를 제공하기 위한 목적 등으로 VM live migration 기술이 활발히 사용되고 있다. 또한 고장 및 장애 상황이 예측되거나 그 징후가 탐지되는 경우, 예방 및 완화 수단으로 활용될 수 있다. 본 논문에서 우리는 두 가지 선제적(proactive) VNF live migration 방법을 제안하며, 첫 번째 방법은 서버 로드밸런싱에 VNF live migration 기법을 사용하며 두 번째 방법은 고장 예측에 기반하여 고장 회피 목적으로 VNF live migration을 사용한다. 선제적 migration을 위한 예측에 머신러닝(기계학습)을 활용하며 실험을 통해 그 실효성을 검증한다. 특히 두 번째 방법에 대해 vEPC (Virtual Evolved Packet Core)의 고장 상황을 case study한 결과를 제시한다.