• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.93-98
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• 2022

Recently, fast storage media such as Optane have emerged, and memory system configurations designed for disk storage should be reconsidered. In this paper, we analyze the effect of the page size on the memory system performances when fast storage is adopted. Based on this, we design a page size model that can guide an appropriate page size for given workloads in virtualized environments. Configuring different page sizes for various workloads is not an easy matter in traditional systems, but due to the widespread adoption of cloud systems, page sizing performed in our model is feasible for virtual machines, which are generated for executing specific workloads. Simulation experiments under various virtual machine scenarios show that the proposed model improves the memory access time significantly by configuring page sizes for given workloads.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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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.

• Journal of KIISE
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• v.43 no.1
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• pp.27-33
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• 2016

Virtualization has become one of the most helpful techniques in computing systems, and today it is prevalent in several computing environments including desktops, data-centers, and enterprises. However, since I/O layers are implemented to be oblivious to the I/O behaviors on virtual machines (VM), there still exists an I/O scalability issue in virtualized systems. In particular, when a multi-queue solid state drive (SSD) is used as a secondary storage, each system reveals a semantic gap that degrades the overall performance of the VM. This is due to two key problems, accelerated lock contentions and the I/O parallelism issue. In this paper, we propose a novel approach, including the design of virtual CPU (vCPU)-dedicated queues and I/O threads, which efficiently distributes the lock contentions and addresses the parallelism issue of Virtio-blk-data-plane in virtualized environments. Our approach is based on the above principle, which allocates a dedicated queue and an I/O thread for each vCPU to reduce the semantic gap. Our experimental results with various I/O traces clearly show that our design improves the I/O operations per second (IOPS) in virtualized environments by up to 155% over existing QEMU-based systems.

• Journal of Digital Contents Society
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• v.15 no.3
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• pp.395-403
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• 2014

Recently webhard services in various applications have been notably increased. In order to adopt some webhard functions into the existing application platform, however, a lot of manpower and cost is necessary. In this paper, we propose webhard API based on cloud storage for building and extending the webhard functions. The proposed system consists of three layers: application, web-hard server, and storage server in which each layer provides its API independently. It is enable the developer to easily extend the webhard functions to the application by using only HTTP request, which provides no limitation of the programming language. Because our webhard API is running on the virtualized cloud storage, it is possible to easily extend the storages and to reduce the maintenance cost. In this paper, we implement all the webhard API and then show the result of adopting the API to a prototype groupware system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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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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• v.14 no.7
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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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• v.15 no.1
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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.