• Journal of Communications and Networks
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• v.5 no.3
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• pp.258-265
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• 2003

Transmission of continuous media streams has been a challenging problem of multimedia service. Lots of works have been done trying to figure out the best solution for this problem, and some works presented the optimal solution for transmitting the stored video using smoothing schemes applied to each individual stream. But those smoothing schemes considered only one stream, not the whole streams being serviced, to apply themselves, which could only achieve local optimum not the global optimum. Most of all, they did not exploit statistical multiplexing gain that can be obtained before smoothing. In this paper, we propose a new smoothing scheme that deals with not an individual stream but the whole streams being serviced simultaneously to achieve the optimal network bandwidth utilization and maximize the number of streams that can be serviced simultaneously. We formally proved that the proposed scheme not only provides deterministic QoS for each client but also maximizes number of clients that can be serviced simultaneously and hence achieves maximum utilization of transmission bandwidth.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.2042-2051
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• 1998

VBR compressed, pre-recorded video is known to exhibit significant, multiple time-scale bit rate variability. To reduce the variability and burstiness of the aggregated transmission rate as low as possible, in this paper, we present an adaptive bandwidth smoothing algorithm, that can be effectively applicalble for VoD services over a shared-medium channel. For these environments where many clients are connected to a single server, by introducing the conventional MVBA(minimum variability bandwidth allocation) algorithm and controlling adaptively the conventional MVBA(minimum variability bandwidth asllocation) algorithm and controlling adaptively the aggregated transmission rate whenever a new clients request is arrived at the server side, the proposed algorithm effectively reduces the burstiness and variability of the aggregated transmission rate. Through computer experiments, it is shown that the proposed method perporms better than the convertional non-aggregated bandwidth smoothing schemes in terms of the peak rate, standard deviation, number of rate changes for the aggregated traffic.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.327-336
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• 2001

This work concerns estimating a regression function, which is not linear, using aggregate data. In much of the empirical research, data are aggregated for various reasons before statistical analysis. In a traditional parametric approach, a linear estimation of the non-linear function with aggregate data can result in unstable estimators of the parameters. More serious consequence is the bias in the estimation of the non-linear function. The approach we employ is the kernel regression smoothing. We describe the conditions when the aggregate data can be used to estimate the regression function efficiently. Numerical examples will illustrate our findings.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.525-537
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• 2016

The paper considers a hybrid model to analyze and forecast time series data based on an empirical mode decomposition (EMD) that accommodates complex characteristics of time series such as nonstationarity and nonlinearity. We aggregate IMFs using the concept of cumulative energy to improve the interpretability of intrinsic mode functions (IMFs) from EMD. We forecast aggregated IMFs and residue with a hybrid model that combines the ARIMA model and an exponential smoothing method (ETS). The proposed method is applied to forecast KOSPI time series and is compared to traditional forecast models. Aggregated IMFs and residue provide a convenience to interpret the short, medium and long term dynamics of the KOSPI. It is also observed that the hybrid model with ARIMA and ETS is superior to traditional and other types of hybrid models.

• East Asian Economic Review
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• v.23 no.3
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• pp.227-260
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• 2019

This paper offers a comprehensive view of international risk sharing and of related policy issues from the perspective of the European Union. The traditional analyses contemplate three risk-sharing channels: the capital markets channel (through cross border portfolio investments), international transfers and the credit markets channel (via savings). Comparative analyses reveal that, on average, about 80% of the shock remains unsmoothed in Europe while only about 18% of the shock is transmitted to consumers within the US. From aggregated figures, there is space for improving, particularly, the cross-border investments channel in Europe. In this sense, the completion of the Banking and Capital Markets Union are expected to boost risk sharing across European member states. We also review new additional issues usually not contemplated by the traditional literature as depreciation, migration and the role of sovereigns and two new additional channels recently considered in the literature: government consumption and the real exchange rate. Finally, we also examine recent analysis related to the geographic distribution of risk sharing.