• Electronics and Telecommunications Trends
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• v.17 no.5 s.77
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• pp.149-156
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• 2002

2000년에 개최된 세계전파통신회의에서는 차기 회의까지 글로벌 환경에서의 고밀도 고정위성업무를 위한 주파수 분배에 대한 연구를 의제로 결정하였다. 이후 ITU-R 회의에서는 17.3GHz 대역 이상의 주파수 대역에서 HDFSS에 적합한 주파수 대역을 연구하고 있는 중이다. 본 고에서에서는 국내 주파수 분배를 고려하여 적절한 HDFSS 주파수 대역을 고찰하고, 외국의 주파수 분배 현황에 대해 비교 검토하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2A
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• pp.181-186
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• 2004

Analysis on sharing between GSO FSS and terrestrial system in the 40㎓ band, related with the problem for sharing between terrestrial services and FSS and identification of HDFSS downlink bands in World Radiocommunication Conference 2003, was practiced by assuming that both systems are operated in Korea. According to results from simulation using the characteristic parameters of GSO FSS and terrestrial FS system in 40 ㎓ described in ITU-R Recommendations, in case that elevation and azimuth angle of antenna of FS station are adjusted to point directly to the geostationary satellite, the GSO system can cause the worst interference to the FS system. This situation is possible to occur in the installation of 40 GHz FS station in urban area where there are high-rise buildings. If high-density FS stations in 40 ㎓ band are operated in the future, interference mitigation techniques to avoid GSO arc should be considered.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.726-734
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• 2015

Relational databases used by structuralizing data are the most widely used in data management at present. However, in relational databases, service becomes slower as the amount of data increases because of constraints in the reading and writing operations to save or query data. Furthermore, when a new task is added, the database grows and, consequently, requires additional infrastructure, such as parallel configuration of hardware, CPU, memory, and network, to support smooth operation. In this paper, in order to improve the web information services that are slowing down due to increase of data in the relational databases, we implemented a model to extract a large amount of data quickly and safely for users by processing Hadoop Distributed File System (HDFS) files after sending data to HDFSs and unifying and reconstructing the data. We implemented our model in a Web-based civil affairs system that stores image files, which is irregular data processing. Our proposed system's data processing was found to be 0.4 sec faster than that of a relational database system. Thus, we found that it is possible to support Web information services with a Hadoop-based big data processing technique in order to process a large amount of data, as in conventional relational databases. Furthermore, since Hadoop is open source, our model has the advantage of reducing software costs. The proposed system is expected to be used as a model for Web services that provide fast information processing for organizations that require efficient processing of big data because of the increase in the size of conventional relational databases.