• 한국컴퓨터정보학회논문지
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• 제24권9호
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• pp.1-8
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• 2019

In this paper, we propose a performance isolation of shared space for virtualized SSD based storage systems, to solve the weakness in a VSSD framework. The proposed scheme adopts a CFQ scheduler and a shared space-based FTL for the fairness and the performance isolation for multiple users on virtualized SSD based storage systems. Using the CFQ scheduler, we ensure SLOs for the storage systems such as a service time, a allocated space, and a IO latency for users on the virtualized storage systems. In addition, to improve a throughput and reduce a computational latency for garbage collection, a shared space-based FTL is adopted to maintain the information of SLOs for users and it manages shared spaces among the users. In our experiments, the proposal improved the throughput of garbage collection by 7.11%, on average, and reduced the computational latency for garbage collection by 9.63% on average, compared to the previous work.

• 한국인터넷방송통신학회논문지
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• 제22권3호
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• pp.93-98
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• 2022

최근 옵테인 등 고속 스토리지의 출현으로 하드디스크에 적합하게 설계된 메모리 시스템 설정에 대한 재고가 필요한 시점에 이르렀다. 본 논문에서는 고속 스토리지의 탑재에 따라 페이지 크기가 메모리 시스템의 성능에 어떠한 영향을 미치는지를 분석하고, 가상화 환경에서 워크로드 상황에 맞게 페이지 크기를 설정할 수 있는 모델을 설계하였다. 전통적인 시스템의 경우 워크로드 별로 페이지 크기를 설정하는 것이 쉬운 일이 아니지만 최근 클라우드 환경의 활성화로 개별 워크로드 수행을 위해 별도의 가상머신이 생성되므로 가상머신이 시작될 때 해당 가상머신의 페이지 크기를 결정할 수 있어 제안한 모델의 효용이 높을 것으로 기대된다. 다양한 가상머신 시나리오에 대한 시뮬레이션 실험을 통해 제안한 모델이 워크로드 상황에 맞게 페이지 크기를 설정하여 메모리 접근 시간을 크게 개선함을 보인다.

• 한국컴퓨터정보학회논문지
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• 제20권10호
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• pp.91-97
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• 2015

In this paper, we propose a MCFQ I/O scheduler that is implemented by modifying the existing Linux CFQ I/O scheduler. MCFQ observes whether the user requested I/O bandwidth weight is well distributed. Based on the I/O bandwidth observation, we improved I/O performance of the existing bandwidth distribution ability by dynamically controlling the I/O time-slice of the virtual machine. The use of SSDs as storage has been increasing dramatically in recent computer systems due to their fast performance and low power usage. As the usage of SSD increases and prices fall, virtualized system administrators can take advantage of SSDs. However, studies on guaranteeing SLA(Service Level Agreement) services when multiple virtual machines share the SSD is still incomplete. In this paper was conducted to improve performance of the bandwidth distribution when multiple virtual machine are sharing a single SSD storage in a virtualized environment. In particular, it was observed that the performance of the bandwidth distribution varied widely when garbage collection occurs in the SSD. In order to reduce performance variance, we add a MoTS(Manager of Time Slice) on existing CFQ I/O scheduler.

• 정보과학회 논문지
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• 제43권1호
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• pp.27-33
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• 2016

오늘날 가상화 기술은 가장 유용하게 사용되는 컴퓨팅 기술 중 하나이며 모든 컴퓨팅 환경에서 널리 활용되고 있다. 그러나 가상화 환경의 I/O 계층들은 호스트 머신의 I/O 동작 방식을 인지하지 못하도록 설계되어 있기 때문에 I/O 확장성 문제는 여전히 해결해야 할 문제로 남아 있다. 특히, 다중 큐 SSD가 보조 기억 장치로 사용될 경우, 증가한 잠금 경쟁과 제한된 I/O 병렬화 문제로 가상 머신은 다중 큐 SSD의 공인된 성능을 활용하지 못하는 문제가 발생한다. 이러한 성능 문제를 해결하기 위해 본 논문에서는 가상 CPU마다 전용 큐와 I/O 스레드를 할당하는 새로운 기법을 제안한다. 제안 기법은 성능 저하의 주요한 원인 중 하나인 잠금 경쟁을 효율적으로 분산시키고 또 다른 원인인 Virtio-blk-data-plane의 병렬화 문제를 해소한다. 제안 기법을 평가한 결과 최신 QEMU 보다 IOPS가 최대 155% 향상되는 것을 확인하였다.

• 디지털콘텐츠학회 논문지
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• 제15권3호
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• pp.395-403
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• 2014

최근 그룹웨어 등 여러 어플리케이션들에서 웹하드 서비스의 필요성이 점점 증가하고 있으나 구축된 어플리케이션에 웹하드 기능을 추가하고 플랫폼을 변경하기 위해서는 많은 인력과 비용이 소모된다. 본 논문은 이를 해결하기 위하여 클라우드 스토리지를 기반으로 웹하드 기능의 구축과 확장이 용이한 웹하드 API를 설계 구현한다. 제안된 시스템은 어플리케이션 - 웹하드 서버 - 스토리지 서버의 3단계로 구성되며, 서버의 각 계층은 독립적으로 분리되어 각각의 API를 제공한다. 따라서 개발자는 어플리케이션에 새로운 웹하드 기능을 추가시켜 확장하고자 할 때, 별도의 기능 구현 없이 HTTP Request 방식의 API를 통해 개발 언어의 제약에서 벗어나 쉽게 다양한 서비스 구축이 가능하다. 또한 스토리지 가상화를 통해 관리자는 다수의 스토리지 서버를 하나의 스토리지처럼 사용할 수 있어 관리가 용이하고, 스토리지의 확장 및 유지 보수비용을 절감할 수 있다. 본 논문에서는 설계된 웹하드 API를 구현하고, 이를 프로토타입 그룹웨어에 적용한 결과를 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권11호
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• pp.3916-3936
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• 2014

Smartphone applications like games, image processing, e-commerce and social networking are gaining exponential growth, with the ubiquity of cellular services. This demands increased computational power and storage from mobile devices with a sufficiently high bandwidth for mobile internet service. But mobile nodes are highly constrained in the processing and storage, along with the battery power, which further restrains their dependability. Adopting the unlimited storage and computing power offered by cloud servers, it is possible to overcome and turn these issues into a favorable opportunity for the growth of mobile cloud computing. As the mobile internet data traffic is predicted to grow at the rate of around 65 percent yearly, even advanced services like 3G and 4G for mobile communication will fail to accommodate such exponential growth of data. On the other hand, developers extend popular applications with high end graphics leading to smart phones, manufactured with multicore processors and graphics processing units making them unaffordable. Therefore, to address the need of resource constrained mobile nodes and bandwidth constrained cellular networks, the computations can be migrated to resourceful servers connected to cloud. The server now acts as a bridge that should enable the participating mobile nodes to offload their computations through Wi-Fi directly to the virtualized server. Our proposed model enables an on-demand service offloading with a decision support system that identifies the capabilities of the client's hardware and software resources in judging the requirements for offloading. Further, the node's location, context and security capabilities are estimated to facilitate adaptive migration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.2815-2839
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• 2020

In a cloud computing paradigm, allocation of various virtualized ICT resources is a complex problem due to the presence of heterogeneous application (MapReduce, content delivery and networks web applications) workloads having contentious allocation requirements in terms of ICT resource capacities (resource utilization, execution time, response time, etc.). This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. However, there is no published research available in this domain that clearly address this research problem and provides research taxonomy for classification of resource allocation techniques including strategic, target resources, optimization, scheduling and power. Hence, the main aim of this paper is to identify open challenges faced by the cloud service provider related to allocation of resource such as servers, storage and networks in cloud computing. More than 70 articles, between year 2007 and 2020, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and are reviewed under clearly defined objectives. Lastly, the evolution of research in resource allocation techniques has also been discussed along with salient future directions in this area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.58-73
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• 2021

Cloud Service Providers (CSPs) enable their users to access Cloud computing and storage services from anywhere in quick and flexible manners through the Internet. With the basis of 'pay-as-you-go' model, it makes the interactions between CSPs and the users play a vital role in shaping the Cloud computing market. A pool of virtualized and dynamically scalable Cloud services that delivered on demand to the users is associated with guaranteed performance and cost-provisioning. It needed a costing scheme for determining suitable charges in order to secure lease pricing of the Cloud services. However, it is hard to meet the satisfied prices for both CSPs and users due to their conflicting needs. Furthermore, there is lack of Service Level Agreements (SLAs) that allowing the users to take part into price negotiating process. The users may lose their interest to use Cloud services while reducing CSPs profit. Therefore, this paper proposes a generic costing scheme for Cloud services using General Equilibrium Theory (GET). GET helps to formulate the price function for various services' factors to match with various demands from the users. It is initially determined by identifying the market circumstances that a general equilibrium will be hold and reached. Specifically, there are two procedures of agreement made in response to (i) established equilibrium supply and demand, and (ii) service price formed and constructed in a price range. The SLAs in our costing scheme is integrated to satisfy both CSPs and users' needs while minimizing their conflicts. The price ranging strategy is deliberated to provide prices' options to the users with respect their budget limit. Meanwhile, the CSPs can adaptively charge based on users' preferences without losing their profit. The costing scheme is testable and analyzed in multi-tenant computing environments. The results from our simulation experiments demonstrate that the proposed costing scheme provides better users' satisfaction while fostering fairness pricing in the Cloud market.