• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.119-125
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• 2019

Recently, it has become a social problem due to fine particles. There are more people wearing masks, weather alerts and disaster notices. Research and policy are actively underway. Meteorologically, the biggest damage caused by fine particles is the inversion layer phenomenon. In this study, we designed a system to warn fine Particles by analyzing inversion layer and wind direction. This weather information system proposes a system that can efficiently perform scalability and parallel processing by using OGC sensor web enablement system and NoSQL storage for sensor control and data exchange.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.26-34
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• 2018

In this paper, we propose a scheduling scheme that can efficiently serve I/O requests having deadlines in flash storage. The I/O requests with deadlines, namely, real-time requests, are assumed to be issued for streaming services of continuous media. Since a Web-based streaming server commonly supports downloads of HTMLs or images, we also aim to quickly process non-real-time I/O requests, together with real-time ones. For this purpose, we adopt the well-known rate-reservation EDF (RR-EDF) algorithm for determining scheduling priorities among mixed I/O requests. In fact, for the use of an EDF-style algorithm, overhead of task's switching should be low and predictable, as with its application of CPU scheduling. In other words, the EDF algorithm is inherently unsuitable for scheduling I/O requests in HDD storage because of highly varying latency times of HDD. Unlike HDD, time for reading a block in flash storage is almost uniform with respect to its physical location. This is because flash storage has no mechanical component, differently from HDD. By capitalizing on this uniform block read time, we compute bandwidth utilization rates of real-time requests from streams. Then, the RR-EDF algorithm is applied for determining how much storage bandwidth can be assigned to non-real-time requests, while meeting deadlines of real-time requests. From this, we can improve the service times of non-real-time requests, which are issued for downloads of static files. Because the proposed scheme can expand flexibly the scheduling periods of streams, it can provide a full usage of slack times, thereby improving the overall throughput of flash storage significantly.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.669-679
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• 2008

With the increasing demands of information sharing and searches via the web, the web search engine has drawn much attention. Although many researches have been done to solve technical challenges to build the web search engine, the issue regarding its query processing system is rarely dealt with. Since the software architecture and operational schemes of the query processing system are hard to elaborate, we here present related techniques implemented on a commercial system. The implemented system is a very large-scale system that can process 5-million user queries per day by using index files built on about 65-million web pages. We implement a multi-level cache scheme to save already returned query results for performance considerations, and the multi-level cache is managed in 4-level cache storage areas. Using the multi-level cache, we can improve the system throughput by a factor of 4, thereby reducing around 70% of the server cost.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.155-168
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• 2008

This paper proposes a relational security model-based RDF Web ontology access control model. The Semantic Web is recognized as a next generation Web and RDF is a Web ontology description language to realize the Semantic Web. Much effort has been on the RDF and most research has been focused on the editor, storage, and inference engine. However, little attention has been given to the security issue, which is one of the most important requirements for information systems. Even though several researches on the RDF ontology security have been proposed, they have overhead to load all relevant data to memory and neglect the situation that most ontology storages are being developed based on relational database. This paper proposes a novel RDF Web ontology security model based on relational database to resolve the issues. The proposed security model provides high practicality and usability, and also we can easily make it stable owing to the stability of the relational database security model.

• Journal of KIISE
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• v.43 no.7
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• pp.725-735
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• 2016

Smart TV uses Webkit as a web browser engine to provide contents such as web surfing, VOD watching, and games. Webkit uses web resources, such as HTML, CSS, JavaScript, and images, in order to run applications. At the start of an application, Webkit loads resources to the memory and creates DOM tree and render tree, which is a time consuming process. However, DOM tree and render tree created by the smart TV application do not change over time because the smart TV application uses web resources stored in a disk. If DOM tree and render tree can be stored and reused, it is possible to reduce loading time of an application. In this paper, we propose FastIO technique that selectively adds persistency to dynamically allocated memory. FastIO reduces overall application loading time by eliminating the process of loading resources from storage, parsing the HTML documents, and creating DOM tree and render tree. Comparison of the application resource loading times indicates that the web browser with FastIO is 7.9x, 44.8x, and 2.9x faster than the legacy web browser in an SSD, Ramdisk, and eMMC environment, respectively.

• Convergence Security Journal
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• v.5 no.1
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• pp.19-27
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• 2005

This paper presents the content regarding electronic medical examination chart and data processing for efficient medical examination and fast treatment by realizing remote medical examination system of mutual conversation type among 3 parties(patient, doctor, pharmacist) on internet base, and establishment of database enabled system integration for efficient data processing in both on-line and off-line mode by interconnecting ASP and SQL on IIS 4.0 web server, consultation between patient and doctor, medical examination on off-line mode, transmission of prescription sheet to the pharmacist designated by patient, preparation of medicine, semieternal storage of medical examination data owing to storage and check of medical examination data, more accurate medical examination and prescription using this medical examination data by patient and doctor, and so on. And, data processing between doctor and pharmacist is differently performed based on class such as general member and charge member, and service access right pursuant to this is endowed, so that certification of each member must follow by all means.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.645-651
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• 2019

At a time when large amounts of data are being poured out, there are many changes in software architecture or data storage patterns because of the nature of the data being written, rather more read-intensive than writing. Accordingly, in this paper, the query model of Command Query Responsibility Segmentation (CQRS) pattern separating the responsibilities of commands and queries is used to implement an efficient high-capacity data lookup system in users' requirements. This paper uses the 2018 temperature, humidity and precipitation data of the Korea Meteorological Administration Open API to store about 2.3 billion data suitable for RDBMS (PostgreSQL) and NoSQL (MongoDB). It also compares and analyzes the performance of systems with CQRS pattern applied from the perspective of the web server (Web Server) implemented and systems without CQRS pattern, the storage structure performance of each database, and the performance corresponding to the data processing characteristics.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.201-206
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• 2019

While many users searched for insurance information online, there were not many cases of contents recommendation researches on insurance companies' websites. Therefore, this study proposed a page recommendation system with high possibility of preference to users by utilizing page visit history of insurance companies' websites. Data was collected by using client-side storage that occurs when using a web browser. Collaborative filtering was applied to research as a recommendation technique. As a result of experiment, we showed good performance in item-based collaborative (IBCF) based on Jaccard index using binary data which means visit or not. In the future, it will be possible to implement a content recommendation system that matches the marketing strategy when used in a company by studying recommendation technology that weights items.

• Journal of KIISE:Information Networking
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• v.27 no.3
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• pp.301-314
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• 2000

As the number of World Wide Web (Web) users grows, Web traffic continues to increase at an exponential rate. Currently, Web traffic is one of the major components of Internet traffic. Also, high bandwodth usage due to Web traffic is observed during peak periods while leaving bandwidth usage idle during off-peak periods. One of the solutions to reduce Web traffic and speed up Web access is through the use of Web caching. Unfortunately, Web caching has limitations for reducing network bandwidth usage during peak periods. In this paper, we focus our attention on the use of a prefetching algorithm for reducing bandwidth during peak periods by using off-peak period bandwidth. We propose a statistical, batch, proxy-side prefetching scheme that improves cache hit rate while only requiring a small amount of storage. Web objects that were accessed many times in previous 24 hours but would be expired in the next 24 hours, are selected and prefetched in our scheme. We present simulation results based on Web proxy and show that this prefetching algorithm can reduce peak time bandwidth using off-peak bandwidth.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.43-59
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• 2019

Today, with the spread of smartphones and the development of social networking services, structured and unstructured big data have stored exponentially. If we analyze them well, we will get useful information to be able to predict data for the future. Large amounts of data need to be collected first in order to analyze big data. The web is repository where these data are most stored. However, because the data size is large, there are also many data that have information that is not needed as much as there are data that have useful information. This has made it important to collect data efficiently, where data with unnecessary information is filtered and only collected data with useful information. Web crawlers cannot download all pages due to some constraints such as network bandwidth, operational time, and data storage. This is why we should avoid visiting many pages that are not relevant to what we want and download only important pages as soon as possible. This paper seeks to help resolve the above issues. First, We introduce basic web-crawling algorithms. For each algorithm, the time-complexity and pros and cons are described, and compared and analyzed. Next, we introduce the state-of-the-art web crawling algorithms that have improved the shortcomings of the basic web crawling algorithms. In addition, recent research trends show that the web crawling algorithms with special purposes such as collecting sentiment words are actively studied. We will one of the introduce Sentiment-aware web crawling techniques that is a proactive web crawling technique as a study of web crawling algorithms with special purpose. The result showed that the larger the data are, the higher the performance is and the more space is saved.