• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1433-1446
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• 2013

In this study, we proposed a methodology to develop Rating Curves for high water level using rainfall generation by the Monte Carlo Simulation (MCS) technique, optimized rainfall-runoff model, and flood routing model in an urban stream. The developed stage discharge Rating Curve based on observed data was contained flow measurement errors and uncertainties. The standard error ($S_e$) for observations was 0.056, and the random uncertainty ($2S_{mr}$) was analyzed by ${\pm}1.43%$ on average, and up to ${\pm}4.27%$. Moreover, it was found that the Rating Curve extensions by way of logarithmic and Stevens methods were overestimated to compare with the urban basin scale. Finally, we confirmed that the high water level extension by random generation of hydrological data using MCS can be reduced uncertainty of the high water level, and it will consider as a more reliable approach for high water level extension. In the near future, this results can be applied to real-time flood alert system for urban streams through construction of the high water level extension system using MCS procedures.

• The KIPS Transactions:PartC
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• v.10C no.5
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• pp.625-634
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• 2003

More than a decade after its initial proposal, deployment of IP Multicast has been limited due to the problem of traffic control in multicast routing, multicast address allocation in global internet, reliable multicast transport techniques etc. Lately, according to increase of multicast application service such as internet broadcast, real time security information service etc., overlay multicast is developed as a new internet multicast technology. In this paper, we describe an overlay multicast protocol and propose fast join mechanism that considers switching of the tree. To find a potential parent, an existing search algorithm descends the tree from the root by one level at a time, and it causes long joining latency. Also, it is try to select the nearest node as a potential parent. However, it can't select the nearest node by the degree limit of the node. As a result, the generated tree has low efficiency. To reduce long joining latency and improve the efficiency of the tree, we propose searching two levels of the tree at a time. This method forwards joining request message to own children node. So, at ordinary times, there is no overhead to keep the tree. But the joining request came, the increasing number of searching messages will reduce a long joining latency. Also searching more nodes will be helpful to construct more efficient trees. In order to evaluate the performance of our fast join mechanism, we measure the metrics such as the search latency and the number of searched node and the number of switching by the number of members and degree limit. The simulation results show that the performance of our mechanism is superior to that of the existing mechanism.