• Journal of Environmental Science International
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• v.23 no.3
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• pp.459-472
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• 2014

Storm surge height in the coastal area of Jeju Island was examined using the Princeton Ocean Model(POM) with a sigma coordinate system. Amongst the typhoons that had affected to Jeju Island for six years(1987 to 2003), the eight typhoons(Maemi, Rusa, Prapiroon, Olga, Yanni, Janis, Gladys and Thelma) were found to bring relatively huge damage. The storm surge height of these typhoons simulated in Jeju harbour and Seogwipo harbour corresponded relatively well with the observed value. The occurrence time of the storm surge height was different, but mostly, it was a little later than the observed time. Jeju harbour showed a higher storm surge height than Seogwipo harbour, and the storm surge height didn't exceed 1m in both of Jeju harbour and Seogwipo harbour. Maemi out of the eight typhoons showed the maximum storm surge height(77.97 cm) in Jeju harbour, and Janis showed the lowest storm surge height(5.3 cm) in Seogwipo harbour.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1945-1949
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• 2006

A storm-induced coastal inundation model (SICIM) is presented to simulate the flood event during typhoon passage that often results in significant rise in sea-level heights especially in the upstream region of the basin. The SICIM is a GIS-based distributed hydrodynamic model, both storm surge and storm water inundations are taken into account. The spatial and temporal distribution of the storm water level and flux are calculated. The model was applied to Jeju Island since it has an isolated watershed that is easy to handle as a first step of model application. Another reason is that it is surrounded by coastal area exposed to storm surge inundation. The model is still advancing and will be the framework of a predictive early inundation warning system.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.447-450
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• 2008

A storm surge is gradually increased in the Korean peninsula. Furthermore, this phenomenon is confined not only the Korean peninsula but also the whole world. A storm surge induced by storm, typhoon, or cyclone is a phenomenon that the water surface elevation is raising by the barometric pressure difference and this water level rising threatens the coastal facilities, settlement, or lives. Most of coastal region in our country are unsafe from this disaster. Even though we are not able to prevent the generation of this phenomenon, we can reduce the damages by investigating the kind of storm surge disaster. Once we finish this investigation, we can reduce the damages by offering the information for risk prior to an invasion of storm surge. This study, we analyzed the previously occurred storm surge damages, and this data can be utilized as a guide for those who live near the coastal region providing the information about the predicting scale of the storm surge

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.4
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• pp.595-602
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• 2009

In this study, a two-dimensional storm surges/tide prediction model called the Storm surges/Tide Operational Model (STORM) was applied as the operational forecast model of the Korea Meteorological Administration (KMA). The operational model results were verified for two years (2006-2007) using observed results from tidal stations. Comparisons of modeled and observed storm surges show that larger differences at the western coast of Korea than at the southern and eastern coasts. The averaged root mean square error between the modeled and observed storm surges height are 0.16 m and 0.10 m in 2006 and 2007, respectively.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.8
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• pp.297-306
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• 2018

In this paper, we address how to apply Apache Storm, a distributed stream processing framework, to InfiniBand, a high performance communication device. An easy way to run Storm on InfiniBand is to simply use IPoIP (IP over InfiniBand). However, this method causes a serious CPU load on the node, which is caused by frequent context switches and buffer copies. To solve this problem, we propose a new communication method using InfiniBand's Remote Direct Memory Access (RDMA) function in Storm. First, we design and implement RJ-Netty (RDMA/JXIO Netty), a new framework that replaces Netty, the legacy framework, to exploit RDMA functionality. Second, we reimplement the related classes so that Storm can use both existing Netty and new RJ-Netty. Third, we extend the JXIO server functionality so as to support multi-threading to maximize the performance of RJ-Netty. Experimental results show that the proposed RJ-Netty significantly reduces CPU load while improving message throughput compared to IPoIB as well as Ethernet. This paper is the first attempt to run Apache Storm on InfiniBand, and we believe that it is an excellent research result that improves the performance of Storm by using InfiniBand RDMA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.2977-2997
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• 2018

In big data era, fresh data grows rapidly every day. More than 30,000 gigabytes of data are created every second and the rate is accelerating. Many organizations rely heavily on real time streaming, while big data stream computing helps them spot opportunities and risks from real time big data. Storm, one of the most common online stream computing platforms, has been used for big data stream computing, with response time ranging from milliseconds to sub-seconds. The performance of Storm plays a crucial role in different application scenarios, however, few studies were conducted to evaluate the performance of Storm. In this paper, we investigate the performance of Storm under different application scenarios. Our experimental results show that throughput and latency of Storm are greatly affected by the number of instances of each vertex in task topology, and the number of available resources in data center. The fault-tolerant mechanism of Storm works well in most big data stream computing environments. As a result, it is suggested that a dynamic topology, an elastic scheduling framework, and a memory based fault-tolerant mechanism are necessary for providing high throughput and low latency services on Storm platform.

• Journal of Ocean Engineering and Technology
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• v.19 no.2 s.63
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• pp.12-18
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• 2005

Typhoon Maemi landed on the southeast coast of Korea and caused a severe storm surge in Jinhae Bay and Masan Bay. The tide gage in Masan Port recorded the storm surge of a maximum of more than 2m and the area of more than 700m from the Seo Hang Wharf was flooded by the storm surge. They had not met such an extremely severe storm surge since the opening of the port. Then storm surge was hindcasted with a numerical model. The typhoon pressure was approximated by Myers' empirical model and super gradient wind around the typhoon eye wall was considered in the wind estimation. The land topography surrounding Jinhae Bay and Masan Bay is so complex that the computed wind field was modified with the 3D-MASCON model. The motion of seawater due to the atmospheric forces was simulated using a one-layer model based on non-linear long wave approximation. The Janssen's wave age dependent drag coefficient on the sea surface was calculated in the wave prediction model WAM cycle 4 and the coefficient was inputted to the storm surge model. The result shows that the storm surge hindcasted by the numerical model was in good agreement with the observed one.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.421-421
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• 2017

In order to secure the safety of coastal areas from the continuous storm surge in Korea, it is important to predict the wave movement and properties accurately during the storm event. To improve the accuracy of the storm simulation, and to quantify coastal risks from the storm event, the dependencies between wave height, wave period, and storm duration should be analyzed. In this study, therefore, copulas were used to develop multivariate statistical models of sea storms. A case study of the east coast of Korea was conducted, and the dependencies between wave height, wave period, water level, storm duration and storm interarrival time were investigated using Kendall's tau correlation coefficient. As a result of the study, only wave height, wave period, and storm duration appeared to be correlated.

• KIISE Transactions on Computing Practices
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• v.23 no.12
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• pp.677-683
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• 2017

Apache Storm is a representative real-time distributed processing system, which is able to process data streams quickly over distributed servers. Storm currently provides several stream grouping methods to distribute data traffic to multiple servers. Among them, the shuffle grouping may cause a processing delay problem and the local-or-shuffle grouping used to solve the problem may cause the problem of concentrating the traffic on a specific node. In this paper, we propose the locality-aware grouping to solve the problems that may arise in the existing Storm grouping methods. Experimental results show that the proposed locality-aware grouping is considerably superior to the existing shuffle grouping and the local-or-shuffle grouping. These results show that the new grouping is an excellent approach considering both the locality and load balancing which are limitations of the existing Storm.

• Ocean and Polar Research
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• v.31 no.4
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• pp.369-377
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• 2009

Performance of the Korea Ocean Research and Development Institute (KORDI) operational storm surge prediction system for the Korean coast is presented here. Results for storm surge hindcasts and forecasts calculations were analyzed. The KORDI storm surge system consists of two important components. The first component is atmospheric models, based on US Army Corps of Engineers (CE) wind model and the Weather Research and Forecasting (WRF) model, and the second components is the KORDI-storm surge model (KORDI-S). The atmospheric inputs are calculated by the CE wind model for typhoon period and by the WRF model for non-typhoon period. The KORDI-S calculates the storm surges using the atmospheric inputs and has 3-step nesting grids with the smallest horizontal resolution of ${\sim}$300 m. The system runs twice daily for a 72-hour storm surge prediction. It successfully reproduced storm surge signals around the Korean Peninsula for a selection of four major typhoons, which recorded the maximum storm surge heights ranging from 104 to 212 cm. The operational capability of this system was tested for forecasts of Typhoon Nari in 2007 and a low-pressure event on August 27, 2009. This system responded correctly to the given typhoon information for Typhoon Nari. In particular, for the low-pressure event the system warned of storm surge occurrence approximately 68 hours ahead.