• KDI Journal of Economic Policy
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• v.28 no.2
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• pp.97-129
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• 2006

This study investigates whether dynamic loan loss provisioning is necessary in Korean banking environments. Under the dynamic provisioning rule banks are required to accumulate additional reserves to general and specific provisionings in preparation for expected loan losses until maturity. This provisioning is most effective in the case that banks tend to recognize less loan losses in the business upturns and/or in the periods of increasing profits. The empirical study, however, shows that banks support procyclicality of loan loss privisioning and earning smoothing behavior over profit fluctuations. These findings suggest that Korea would not seriously need the introduction of dynamic loan loss provisioning. But this policy implication does not seem robust in view that the recent experience shows the countercyclicality of loan loss provisioning practices and negative correlation between earnings and provisioning after financial restructuring was completed. This result is partly attributable to vigorous shareholder activism because of high foreign ownership of most commercial banks. Once it is true that bank management is more interested in short-term performances, current loan loss provisioning would have attributes of impairing capital adequacy, hence strengthening loan loss provisiong requirements.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.555-566
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• 2012

The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2840-2853
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• 2015

A major challenge in network service providers is to provide adequate resources in service level agreements based on forecasts of future demands. In this paper, we address the problem of capacity provisioning in a network subject to demand uncertainty such that a network coded multicast is applied as the data delivery mechanism with limited budget to purchase extra capacity. We address some particular type of uncertainty sets that obtain a tractable constrained capacity provisioning problem. For this reason, we first formulate a mathematical model for the problem under uncertain demand. Then, a robust optimization model is proposed for the problem to optimize the worst-case system performance. The robustness and effectiveness of the developed model are demonstrated by numerical results. The robust solution achieves more than 10% reduction and is better than the deterministic solution in the worst case.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1119-1137
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• 2017

This study assessed the water provisioning and climate mitigation ecosystem services of the urban forest in Seoul and Gyeonggi-do. The ecosystem service assessment is conducted based on natural function, natural function and population, and natural function and the beneficiary of the ecosystem service. Then, the impact of climate change on ecosystem services is analyzed to figure out the sensitivity of the impact on the beneficiary when the natural function of forest destroys under climate change. Gyeonggi-do has higher function-based water provisioning ecosystem service than Seoul. And population-based water provisioning ecosystem service appears to be higher in the densely populated area. On the other hand, beneficiary-based water provisioning ecosystem service by applying both natural water supply function and beneficiary distribution appears different with the result of population-based water provisioning service assessment. In other words, regions with high beneficiary population show higher ecosystem service than those with a low beneficiary population even though they have the same water storage function. In addition, climate change has a negative impact on the water provisioning ecosystem service. Under climate change, water provisioning service is expected to decrease by 26%. For climate mitigation service, regions close to the forest seem to have a low temperature, which indicates their high climate mitigation service. The center of the city with high beneficiary population shows high beneficiary-based ecosystem service. The climate change impacts the forest growth to decrease which affect the beneficiary-based climate mitigation ecosystem service to decrease by 33%. From this study, we conclude that beneficiary-based function and ecosystem service assessment is needed as well as the supply-based classification of forest function suggested by Korea Forest Service. In addition, we suggest that not only supply-based function classification and ecosystem service assessment but also beneficiary-based function classification and ecosystem service assessment is needed for managing the urban forest, which has been destroyed by climate change. This will contribute to revaluing cases where a forest with low natural function but high beneficiary-based ecosystem service, which is not considered under the current forest function-based assessment system. Moreover, this could assist in developing a suitable management plan for the urban forest.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5271-5289
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• 2016

On large-scale data analysis platforms deployed on cloud infrastructures over the Internet, the instability of the data transfer time and the dynamics of the processing rate require a more sophisticated data distribution scheme which maximizes parallel efficiency by achieving the balanced load among participated computing elements and by eliminating the idle time of each computing element. In particular, under the constraints that have the real-time and limited data buffer (in-memory storage) are given, it needs more controllable mechanism to prevent both the overflow and the underflow of the finite buffer. In this paper, we propose an auto regulated data provisioning model based on receiver-driven data pull model. On this model, we provide a synchronized data replenishment mechanism that implicitly avoids the data buffer overflow as well as explicitly regulates the data buffer underflow by adequately adjusting the buffer resilience. To estimate the optimal size of buffer resilience, we exploits an adaptive buffer resilience control scheme that minimizes both data buffer space and idle time of the processing elements based on directly measured sample path analysis. The simulation results show that the proposed scheme provides allowable approximation compared to the numerical results. Also, it is suitably efficient to apply for such a dynamic environment that cannot postulate the stochastic characteristic for the data transfer time, the data processing rate, or even an environment where the fluctuation of the both is presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.199-207
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• 2010

In this paper considered is the provisioning quantity determination problem of consumable concurrent spare parts (CSP) of a new equipment system to minimize the procurement cost under the operational availability constraint. When a part fails, repair of the failed part is impossible and the part is replaced and cannibalization is allowed. The failure of a part is assumed to follow a Poisson process and the operational availability in CSP is defined. The solution procedure consists of two parts. Firstly, a heuristic algorithm is developed under the assumption that the failure rate is constant during the CSP period. Secondly, proposed is a simulation search procedure which improves the heuristic solution to the near optimal solution in a reasonable amount of time. An illustrative example is shown to explain the solution procedure.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.12
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• pp.83-93
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• 2003

Differentiated service networks, based on bandwidth broker, perform the control and management of QoS provisioning for the QoS guaranteed services, However, the centralized bandwidth broker model has a scalability problem since it has centralized resource management for the admission control function of all call attempts, Therefore, in this paper, we proposea novel adaptive admission control mechanism according to the attempted call status for enhancing the scalability under the centralized bandwidth broker model in IP differentiated service networks, The proposed mechanism decouples the function of admission control from the bandwidth broker, So, the ingress edge node performs the admission control and the bandwidth broker performs the resource management and QoS provisioning, We also introduce an edge-to-edge path concepts and the ingress edge node performs the admission control under the allocated bandwidth to eachpath. The allocated bandwidth per path adaptively varies according to the status of the attempted calls, This mechanism can significantly reduce the number of communication message between the bandwidth broker and each edge node in the network and increase the bandwidth utilization via adaptable resource allocation, In this paper we study the adaptive admission control operation and show the efficient and extensive improvement through the performance evaluation.

• 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.