• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.158-167
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• 2017

Internet-based social and interactive video applications have become major constituents of the envisaged applications for next-generation multimedia networks. However, inherently dynamic network conditions, together with varying user expectations, pose many challenges for resource allocation mechanisms for such applications. Yet, in addition to addressing these challenges, service providers must also consider how to mitigate their operational costs (e.g., energy costs, equipment costs) while satisfying the end-user quality of service (QoS) expectations. This paper proposes a heuristic solution to the problem, where the energy incurred by the applications, and the monetary costs associated with the service infrastructure, are minimized while simultaneously maximizing the average end-user QoS. We evaluate the performance of the proposed solution in terms of serving probability, i.e., the likelihood of being able to allocate resources to groups of users, the computation time of the resource allocation process, and the adaptability and sensitivity to dynamic network conditions. The proposed method demonstrates improvements in serving probability of up to 27%, in comparison with greedy resource allocation schemes, and a several-orders-of-magnitude reduction in computation time, compared to the linear programming approach, which significantly reduces the service-interrupted user percentage when operating under variable network conditions.

• Geomechanics and Engineering
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• v.14 no.1
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• pp.9-17
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• 2018

Brazilian splitting tests, uniaxial compression tests and triaxial compression tests are carried out on the coal samples cored from Shanxi group $II_1$ coal seam of Jiaozuo coal mine, Henan province, China, to obtain their property parameters. Considering the bedding has notable effect on the property parameter of coal, the samples with different bedding angles are prepared. The effects of bedding on the anisotropic characteristics of the coal seam are investigated. A geological geomechanical model is built based on the geology characteristics of the Jiaozuo coal mine target reservoir to study the effects of bedding on the fracture propagations during hydraulic fracturing. The effects of injection pressure, well completion method, in-situ stress difference coefficient, and fracturing fluid displacement on the fracture propagations are investigated. Results show bedding has notable effects on the property parameters of coal, which is the key factor affecting the anisotropy of coal. The hydraulic cracks trends to bifurcate and swerve at the bedding due to its low strength. Induced fractures are produced easily at the locations around the bedding. The bedding is beneficial to form a complicated fracture network. Experimental and numerical simulations can help to understand the effects of bedding on hydraulic fracturing in coalbed methane reservoirs.

• The KIPS Transactions:PartC
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• v.14C no.7
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• pp.559-570
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• 2007

In this paper, we define a Hose-NSIS-QoSM, which reserves and manages resources according to the hose based resource provisioning mechanisms for supporting the VPN QoS(Quality of Service) using the NSIS(Next Step in Signaling) signaling protocol. Specifically, we specify the NSIS message objects, the structures of QoS NSLP(NSIS Signaling Layer Protocol)/NTLP(NSIS Transport Layer Protocol)/RMF(Resource Management Function) state tables and the processing of the signaling messages in NSIS nodes. Also, we compare the Hose-NSIS-QoSM with the Hose-RSVP-TE-QoSM that supports the hose based VPN QoS in the MPLS networks using the extended RSVP-TE mechanism.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.590-601
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• 2023

University books are an important information resource. University book resources can be shared not only in the traditional paper form, but also electronic form under the background of the Internet. In order to better manage the sharing of electronic book resources in universities, this study put forward three resource sharing strategies: centralized sharing strategy, distributed sharing strategy, and centralized-distributed sharing strategy by analyzing the combined development of books and the Internet as well as the significance and development of book resource sharing. The centralized sharing strategy, however simple, was difficult to handle large traffic; while the resource nodes were independent and self-consistent, the distributed sharing strategy was not easy to find and had a high repetition rate. Combining the advantages of both strategies, the centralized-distributed sharing strategy was more suitable for the heterogeneous form of university book sharing. Finally, a teaching resources sharing platform for university libraries was designed based on the strategy of centralized and distributed sharing, and three interfaces including platform login, resource search, and resource release were displayed. The results of the simulated comparison experiment showed that centralized and distributed sharing strategies had limitations in resource searching and had low efficiencies; the efficiency of the centralized strategy reduced with an increase in search subjects; however, the centralized-distributed sharing strategy was able to search more resources efficiently and main stability.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.27-42
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• 2009

In realizing ubiquitous computing, techniques of efficiently using the limited resource at client such as mobile devices are required. With a mobile device with limited amount of memory, the techniques of XML stream query processing should be employed to process queries over a large volume of XML data. Recently, several techniques were proposed which fragment XML documents into XML fragments and stream them for query processing at client. During query processing, there could be great difference in resource usage (query processing time and memory usage) depending on how the source XML documents are fragmented. As such, an efficient fragmentation technique is needed. In this paper, we propose an XML fragmentation technique whereby resource efficiency in query processing at client could be enhanced. For this, we first present a cost model of query processing over XML fragment stream. Then, we propose an algorithm for resource-efficient XML fragmentation. Through implementation and experiments, we showed that our fragmentation technique outperformed previous techniques both in processing time and memory usage. The contribution of this paper is to have made the techniques of query processing over XML fragment stream more feasible for practical use.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.1
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• pp.1-9
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• 2007

At present various methods relating resource access control in grid environment are being studied. Most of the access authorization to grid resource is designed fit to the attributes and the role of user. But resource access control is to be made in the respect of business model to activate grid. Therefore this study suggests a model that can operate resource access control driven by grid accounting information. On the base of collection of accounting information about grid job, processing cost is yielded. If the user's available fund is less than processing cost, it gets to control grid job by the resource access control policy. Finally when grid job is completed, user is assigned to pay the charges for using resource of supplier. Then resource provider gets to supply stable resource in grid by participating it voluntarily to use idle resource. This study is esteemed to realize utility computing environment correspondent to economic principle by ensuring resource access policy of organizations which participate in grid.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1569-1586
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• 2015

This paper considers the optimal cell association and resource allocation for load balancing in a heterogeneous cellular network subject to user's quality-of-service (QoS) constraints. We adopt the proportional fairness (PF) utility maximization formulation which also accommodates the QoS constraints in terms of minimum rate requirements. With equal resource allocation this joint optimization problem is either infeasible or requires relaxation that yields a solution which is difficult to implement. Nevertheless, we show that this joint optimization problem can be effectively solved without any priori assumption on resource allocation and yields a cell association scheme which enforces single BS association for each user. We re-formulated the joint optimization problem as a network-wide resource allocation problem with cardinality constraints. A reweighted heuristic l₁-norm regularization method is used to obtain a sparse solution to the re-formulated problem. The cell association scheme is then derived from the sparsity pattern of the solution, which guarantees a single BS association for each user. Compared with the previously proposed method based on equal resource allocation, the proposed framework results in a feasible cell association scheme and yields a robust solution on resource allocation that satisfies the QoS constraints. Our simulations illustrate the impact of user's minimum rate requirements on cell association and demonstrate that the proposed approach achieves load balancing and enforces single BS association for users.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.333-344
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• 2022

In a container-based cloud environment, multiple containers can share a graphical processing unit (GPU), and GPU sharing can minimize idle time of GPU resources and improve resource utilization. However, in a cloud environment, GPUs, unlike CPU or memory, cannot logically multiplex computing resources to provide users with some of the resources in an isolated form. In addition, containers occupy GPU resources only when performing GPU operations, and resource usage is also unknown because the timing or size of each container's GPU operations is not known in advance. Containers unrestricted use of GPU resources at any given point in time makes managing resource contention very difficult owing to where multiple containers run GPU tasks simultaneously, and GPU tasks are handled in black box form inside the GPU. In this paper, we propose a container management technique to prevent performance degradation caused by resource competition when multiple containers execute GPU tasks simultaneously. Also, this paper demonstrates the efficiency of container management techniques that analyze and propose the problem of degradation due to resource competition when multiple containers execute GPU tasks simultaneously through experiments.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.5
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• pp.123-136
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• 2021

RPC (Remote Procedure Call)-based Graphics Processing Unit (GPU) virtualization technology is one of the technologies for sharing GPUs with multiple user virtual machines. However, in a cloud environment, unlike CPU or memory, general GPUs do not provide a resource isolation technology that can limit the resource usage of virtual machines. In particular, in an RPC-based virtualization environment, since GPU tasks executed in each virtual machine are performed in the form of multi-process, the lack of resource isolation technology causes performance degradation due to resource competition. In addition, the GPU memory competition accelerates the performance degradation as the resource demand of the virtual machines increases, and the fairness decreases because it cannot guarantee equal performance between virtual machines. This paper, in the RPC-based GPU virtualization environment, analyzes the performance degradation problem caused by resource contention when the GPU memory requirement of virtual machines exceeds the available GPU memory capacity and proposes a GPU memory management technique to solve this problem. Also, experiments show that the GPU memory management technique proposed in this paper can improve the performance of GPGPU tasks.

• Journal of Information Processing Systems
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• v.5 no.2
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• pp.87-96
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• 2009

Grid computing is a new technology which involves efforts to create a huge source of processing power by connecting computational resources throughout the world. The key issue of such environments is their resource allocation and the appropriate job scheduling strategy. Several approaches to scheduling in these environments have been proposed to date. Market driven scheduling as a decentralized solution for such complicated environments has introduced new challenges. In this paper the bidding problem with regard to resources in the reverse auction resource allocation model has been investigated and the new bidding strategies have been proposed and investigated.