• KIPS Transactions on Computer and Communication Systems
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• v.4 no.3
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• pp.81-84
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• 2015

Cloud service is one of major technologies in modern IT business. Due to the dynamics of user demands, service providers need VM(Virtual Machine) provisioning mechanism to predict the amount of resources demanded by cloud users for the next service and to prepare the resources. VM provisioning provides the QoS to cloud user and maximize the revenue of a service provider by minimizing the expense. In this paper, we propose a new VM provisioning technique to minimize the total expense of a service provider by minimizing the expected value of the expense based on the predicted demands of users. To evaluate the effectiveness of our prediction technique, we compare the total expense of our technique with these of the other prediction techniques with a series of real trace data.

• Journal of Internet of Things and Convergence
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• v.9 no.4
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• pp.9-14
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• 2023

Recently, resource optimization research has been actively conducted in enterprises and data centers to manage the rapid growth of big data. In particular, thin provisioning, which allocates a large number of resources compared to fixedly allocated storage resources, has the effect of reducing initial costs, but as the number of resources actually used increases, the cost effectiveness decreases and the management cost for allocating resources increases. In this paper, we propose a technique that divides the physical blocks of flash memory into single-bit cells and multi-bit cells, formats them with a hybrid technique, and manages them by dividing frequently used hot data and infrequently used cold data. The proposed technique has the advantage that the physical and allocated resources are the same, such as thick provisioning, and can be used without additional cost increase, and the underutilized resources can be managed in multi-bit cell blocks, such as thin provisioning, which can allocate more resources than typical storage devices. Finally, we estimated the resource optimization effectiveness of the proposed technique through experiments based on simulations.

• Journal of the Korea Society for Simulation
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• v.22 no.1
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• pp.77-86
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• 2013

Cloud computing is one of the distributed computing environments and utilizes several computing resources. Cloud environment uses a virtual machine to process a requested job. To balance a workload and process a job rapidly, cloud environment uses a provisioning technique and assigns a task with a status of virtual machine. However, a scheduling method for cloud computing requires a definition of virtual machine availabilities, which have an obscure meaning. In this paper, we propose Fuzzy logic driven Virtual machine Provisioning scheduling using Resource Evaluation(FVPRE). FVPRE analyzes a state of every virtual machine and actualizes a value of resource availability. Thus FVPRE provides an efficient provisioning scheduling with a precise evaluation of resource availability. FVPRE shows a high throughput and utilization for job processing on cloud environments.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1625-1627
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• 2015

클라우드 컴퓨팅의 가상화된 인프라 기반 위에서 IT 자원 및 애플리케이션 서비스를 관리하고 배포하는 작업이 클라우드 프로비저닝이다. 본 논문에서는 IT 자원을 할당함에 있어 전문적인 지식을 가진 관리자의 개입을 최소화하기 위해 일련의 자원 할당 작업을 자동화하였다. 자동화된 자원 프로비저닝을 통해 관리자는 특정 전문 지식 없이도 자원 할당 및 배포가 가능해져 이용자의 요구를 보다 신속하게 처리할 수 있게 되었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.155-156
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• 2013

VM 간섭은 VM 프로비저닝을 할 때 예상된 VM 의 컴퓨팅 자원이 실제와 다르지 않도록 하기 위해 반드시 고려되어야 할 사항이다. 이에 본 논문에서는 예상된 VM 의 컴퓨팅 자원을 사용자가 보장받을 수 있도록 랜덤 워크를 이용해 간섭을 고려한 필요 자원을 구하는 방법에 대해 다루고 있다.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.139-147
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• 2011

There is a growing tendency toward a vehicle demand and a utilization of traffic information systems. Due to various kinds of traffic information systems and increasing of communication data, the traffic information service requires a very high IT infrastructure. A cloud computing environment is an essential approach for reducing a IT infrastructure cost. And the traffic information service needs a provisioning scheduling method for managing a resource. So we propose a provisioning scheduling with conditional probability inference (PSCPI) for the traffic information service on cloud environment. PSCPI uses a naive bayse inference technique based on a status of a virtual machine. And PSCPI allocates a job to the virtual machines on the basis of an availability of each virtual machine. Naive bayse based PSCPI provides a high throughput and an high availability of virtual machines for real-time traffic information services.

• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.547-558
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• 2016

Construction of multi-site Cloud Infrastructure with OpenStack, the most popular cloud open source project with various ICT infrastructure technologies, has operational inefficiency due to installation complexity and geographical limitation. To address this inefficiency, we gradually developed automated installation/configuration tools to automate installation/configuration of Linux and OpenStack by complying with DevOps methodology over a multi-site OpenStack testbed called OF@KOREN SmartX Playground. However, the pre-developed installation tools can be used only for limited cases. Therefore, we designed and developed a prototype of SmartX Provisioning Framework which could conducts Playground-wide provisioning flexibly by following three steps of resource management in Software-defined Infrastructure. We verified the efficiency of the provisioning functionality of the framework by demonstrating an example of automated multi-site cloud construction.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.89-98
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• 2007

In these days, the use of context in application running on mobile devices such as PDAs and smart Phone has become a crucial requirement for several research areas, including ubiquitous computing. mobile computing. Previous middlewares which support context provisioning uses single strategy. But, this paper proposed middleware integrated multiple strategies for context provisioning, namely internal sensors-based, external infrastructure-based, and distributed provisioning in ad hoc networks. Applications can query needed context items using SQL like context query language and require context information to use different provisioning mechanisms depending on resource availability and presence of external infrastructures.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.39-48
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• 2013

A cloud system has to deal with highly variable workloads resulting from dynamic usage patterns in order to keep the QoS within the predefined SLA. Aside from the aspects regarding services, another emerging concern is to keep the energy consumption at a minimum. This requires the cloud providers to consider energy and performance trade-off when allocating virtualized resources in cloud data centers. In this paper, we propose a resource provisioning approach based on dynamic thresholds to detect the workload level of the host machines. The VM selection policy uses utilization data to choose a VM for migration, while the VM allocation policy designates VMs to a host based on its service reputation. We evaluated our work through simulations and results show that our work outperforms non-power aware methods that don't support migration as well as those based on static thresholds and random selection policy.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.41-44
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• 2014

최근 클라우드 컴퓨팅에 관련된 기술이 각광을 받으면서, 기존에 인터넷을 통해 제공되던 다양한 서비스들이 클라우드 컴퓨팅 플랫폼 환경으로 이동하고 있다. 이를 통해 사용자들에게는 좀 더 편리하고 유연한 서비스를 제공하고 서비스 제공자들에게는 기존 관리 비용의 절감을 할 수 있게 되었다. 하지만 현재 폭발적인 수요의 증가로 인해, 기존의 자원 활용도의 극대화를 목적으로 고안된 자원 분배 기법들에 대한 여러 한계점이 나타나게 되었다. 본 논문에서는 이러한 문제점들을 해결하고자 클라우드 컴퓨팅 환경에서 Qos를 기반으로 사용자나 서비스 제공자의 비용적인 측면을 고려한 자원분배를 통해 서비스를 제공시 사용자 요구를 만족시키고 동시에 서비스 공급자에게는 비용 효율적인 프로비저닝(Provisioning)기법을 제안하고자 한다. 실험 결과 기존의 자원 활용도에 중점을 둔 기법보다 사용자 요청에 대한 응답 속도가 8.35% 향상되었으며, 컴퓨터 자원 유지 관련 비용면에서도 기존 대비 11.31% 절감 효과를 가져오는 것을 확인 할 수 있었다.