• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.5-6
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• 2012

본 논문에서는 가상머신에서 수행되는 어플리케이션의 서비스 품질을 보장하고, 클라우드 클러스터의 운영비용을 절감시킬 수 있는 자원 할당 감축기법을 제안한다. 이 기법은 가상머신의 자원 사용량 변화 추세를 분석하고 이를 토대로 확률적인 접근을 사용하여 새로운 자원 할당 감축량을 결정한다. 가상머신의 자원 사용량이 할당량을 초과하면 가상머신의 이주가 필요하다. 이때 발생하는 다운타임동안 가상머신의 어플리케이션은 서비스를 수행할 수 없기 때문에 클라우드 시스템의 성능이 저하된다. 따라서 성능평가에서는 가상머신의 자원 사용량이 할당량을 초과하는 횟수를 측정하여 Greedy 기법과 비교 평가함으로써 제안한 기법이 자원 할당 감축에 우수함을 검증한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4165-4187
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• 2016

As an emerging technology, cloud computing is a revolution in information technology that attracts significant attention from both public and private sectors. In this paper, we proposed a dynamic approach for live migration to obviate overloaded machines. This approach is applied on OpenStack, which rapidly grows in an open source cloud computing platform. We conducted a cost-aware dynamic live migration for virtual machines (VMs) at an appropriate time to obviate the violation of service level agreement (SLA) before it happens. We conducted a preemptive migration to offload physical machine (PM) before the overload situation depending on the predictive method. We have carried out a distributed model, a predictive method, and a dynamic threshold policy, which are efficient for the scalable environment as cloud computing. Experimental results have indicated that our model succeeded in avoiding the overload at a suitable time. The simulation results from our solution remarked the very efficient reduction of VM migrations and SLA violation, which could help cloud providers to deliver a good quality of service (QoS).

• KIISE Transactions on Computing Practices
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• v.22 no.6
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• pp.278-283
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• 2016

Due to explosive increase in the amount of data produced recently, cloud storage system is required to offer high and stable performance. However, VM (Virtual Machine) migration may result in lowered storage service performance. Especially, in an environment where the host-side flash cache is used in a cloud system, the existing warmed up cache is lost and the problematic cold start begins at a new cache due to a VM migration. In this paper, we first demonstrate and analyze the cold start problem and then propose Cachemior (Cache migrator) which enables efficient hot start of the flash cache.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.61-65
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• 2012

Many public organizations have been adopting and operating various servers. These servers run on Windows, Unix, and Linux operating systems that generally use less than 10% of their capacity. For migrating a public organization to cloud computing, we must first virtualize the server environment. This article proposes a strategy for server virtualization that the National IT Industry Promotion Agency (NIPA) has done and describes the effects of a public organization migrating to cloud computing. The NIPA Computer Center planned an effective virtualization migration on various servers. This project of virtualization migration was conducted with the existing policy of separate x86 servers and Unix servers. There are three popular approaches to server virtualization: a virtual machine model, a paravirtual machine model, and virtualization at the operating system layer. We selected a VMware solution that uses the virtual machine model. We selected servers for virtualization in the following manner. Servers were chosen that had the highest rate of service usage and CPU usage and had been operating for five years or more. However, we excluded servers that require 80% or greater rates of CPU usage. After adopting the server virtualization technique, we consolidated 32 servers into 3 servers. Virtualization is a technology that can provide benefits in these areas: server consolidation and optimization, infrastructure cost reduction and improved operational flexibility, and implementation of a dual computing environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4320-4333
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• 2017

Energy-efficient virtual resource allocation algorithm has become a hot research topic in cloud computing. However, most of the existing allocation schemes cannot ensure each type of resource be fully utilized. To solve the problem, this paper proposes a virtual machine (VM) allocation algorithm on the basis of multi-dimensional resource, considering the diversity of user's requests. First, we analyze the usage of each dimension resource of physical machines (PMs) and build a D-dimensional resource state model. Second, we introduce an energy-resource state metric (PAR) and then propose an energy-aware multi-dimensional resource allocation algorithm called MRBEA to allocate resources according to the resource state and energy consumption of PMs. Third, we validate the effectiveness of the proposed algorithm by real-world datasets. Experimental results show that MRBEA has a better performance in terms of energy consumption, SLA violations and the number of VM migrations.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1735-1738
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• 2010

가상화는 하나의 물리적 시스템을 논리적으로 분할해 자원 공유의 효율성을 극대화하는 기술이다. 하지만 가상화에 필수적인 시스템의 추상화는 자원 관리의 복잡도를 증가시켜 하드웨어 장치의 로드 발생을 야기한다는 문제점이 있다. 가상 머신 마이그레이션(migration)은 로드를 발생시키는 가상 머신을 자원적 여유가 있는 시스템으로 이동시키는 기술이며, 기존의 기법들은 메모리상의 실행 컨텍스트의 이동 비용을 최소화하기 위한 방법에 초점을 맞추고 있다. 하지만 네트워크를 통한 스토리지의 공유가 어려운 WAN(wide area network) 환경에서는 실행 컨텍스트뿐만 아니라 가상 머신 이미지 자체의 이동이 불가피하며, 이는 많은 비용을 발생시킨다. 따라서 본 연구에서는 가상 머신간 파일 블록 공유를 통한 WAN 환경에서의 효율적인 가상 머신 마이그레이션 기법을 제안하고, 실험을 통해 제안 기법에 대한 분석 및 평가를 실시하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.35-43
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• 2020

Cloud computing integrates computing resources such as servers, storage, and networks with virtualization technology to provide suitable services according to user needs. Due to the structural characteristics of sharing physical resources based on virtualization technology, threats to availability can occur, so it is essential to respond to availability threats in cloud computing. Existing over-provisioning method is not suitable because it can generate idle resources and cause under-provisioning to degrade or disconnect service. System resources must be allocated in real-time according to the system load to guarantee the cloud system's availability. Through appropriate management measures, it is necessary to reduce the system load and increase the performance of the system. This paper analyzes the work response time according to the allocation or migration of virtual machines and discusses an efficient resource management method considering the system load.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.103-111
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• 2016

Offloading tasks from mobile devices to available cloud servers were improved since the introduction of the cloudlet. With the implementation of dynamic offloading algorithms, mobile devices can choose the appropriate server for the set of tasks. However, current task distribution approaches do not consider the number of VM, which can be a critical factor in the decision making. This paper proposes a dynamic task distribution on clustered data centers. A proportional VM migration approach is also proposed, where it migrates virtual machines to the cloud servers proportionally according to their allocated CPU, in order to prevent overloading of resources in servers. Moreover, we included the resource capacity of each data center in terms of the maximum CPU in order to improve the migration approach in cloud servers. Simulation results show that the proposed mechanism for task distribution greatly improves the overall performance of the system.

• KIISE Transactions on Computing Practices
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• v.22 no.9
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• pp.473-478
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• 2016

Server virtualization provides abstraction of physical resources to users and thus accomplishes high resource utilization and flexibility. However, the characteristics of server virtualization, such as the limited number of physical resources shared by virtual machines, can cause problems, mainly performance interference. The performance interference is caused by the fact that the CPU scheduler running on the host operating system schedules virtual machines without considering the characteristics of the virtual machine's internal process. To address performance interference, a number of research activities to improve performance interference have been conducted, but do not deal with the fundamental analysis of performance interference. In this paper, in order to analyze the cause of performance interference, we carry out profiling in a variety of scenarios in a virtualized environment based on KVM. As a result, we analyze the phenomenon of the performance interference in terms of CPU scheduling and propose an efficient scheduling solution.