• The KIPS Transactions:PartA
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• v.16A no.4
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• pp.263-272
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• 2009

For implementing the ubiquitous computing environments with smart home infrastructures, various research on the home network have been performed by several research institutes and companies. Due to the various home network middleware that are developed recently, the standardization of the home network middleware is being delayed and it calls for the middleware bridge which solves the interoperability problem among the heterogeneous middlewares. Now the research on the scheme for interoperability and the development of the various bridges are in progress, such as one-to-one bridge supporting interoperability between two middlewares and one-to-many bridge supporting interoperability among the multi-middlewares. However, existing systems and schemes does not consider the dynamic extensibility and performance that is particularly needed in the smart home environments. The middleware bridge should provide bridge extensibility with zero-configuration for non-expert users. It should also provide the load balancing scheme for efficient and proper traffic distribution. In this paper, we propose a Multi-Middleware Bridge(MMB) for dynamic extensibility and load balancing in home network environments. MMB provides bridge scalability and load balancing through the distributed system structure. We also verify the features such as interoperability, bridge extensibility, and the performance of the load balancing algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1277-1286
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• 2018

In this paper, we provide flexible scalability of computing resources in cloud environment and Apache Hadoop based cloud environment for analysis of public medical information big data. In fact, it includes the ability to quickly and flexibly extend storage, memory, and other resources in a situation where log data accumulates or grows over time. In addition, when real-time analysis of accumulated unstructured log data is required, the system adopts Hadoop-based analysis module to overcome the processing limit of existing analysis tools. Therefore, it provides a function to perform parallel distributed processing of a large amount of log data quickly and reliably. Perform frequency analysis and chi-square test for big data analysis. In addition, multivariate logistic regression analysis of significance level 0.05 and multivariate logistic regression analysis of meaningful variables (p<0.05) were performed. Multivariate logistic regression analysis was performed for each model 3.

• Journal of KIISE:Information Networking
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• v.30 no.5
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• pp.631-640
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• 2003

Because of multi-hop wireless communication, P2P applications in ad hoc networks suffer poor performance. We Propose neighbor caching strategy to overcome this shortcoming and show it is more efficient than self caching that nodes store data in theirs own cache individually. A node can extend its caching storage instantaneously with neighbor caching by borrowing the storage from idle neighbors, so overcome multi-hop wireless communications with data source long distance away from itself. We also present the ranking based prediction that selects the most appropriate neighbor which data can be stored in. The node that uses the ranking based prediction can select the neighbor that has high possibility to keep data for a long time and avoid caching the low ranked data. Therefore the ranking based prediction improves the throughput of neighbor caching. In the simulation results, we observe that neighbor caching has better performance, as large as network size, as long as idle time, and as small as cache size. We also show the ranking based prediction is an adaptive algorithm that adjusts times of data movement into the neighbor, so makes neighbor caching flexible according to the idleness of nodes

• KIISE Transactions on Computing Practices
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• v.21 no.11
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• pp.681-688
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• 2015

The k nearest neighbor (k-NN) graph construction is an important operation with many web-related applications, including collaborative filtering, similarity search, and many others in data mining and machine learning. Despite its many elegant properties, the brute force k-NN graph construction method has a computational complexity of $O(n^2)$, which is prohibitive for large scale data sets. Thus, (Key, Value)-based distributed framework, MapReduce, is gaining increasingly widespread use in Locality Sensitive Hashing which is efficient for high-dimension and sparse data. Based on the two-stage strategy, we engage the locality sensitive hashing technique to divide users into small subsets, and then calculate similarity between pairs in the small subsets using a brute force method on MapReduce. Specifically, generating a candidate group stage is important since brute-force calculation is performed in the following step. However, existing methods do not prevent large candidate groups. In this paper, we proposed an efficient algorithm for approximate k-NN graph construction by regrouping candidate groups. Experimental results show that our approach is more effective than existing methods in terms of graph accuracy and scan rate.

• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.317-326
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• 2010

Nowadays, transmission bandwidth for network traffic is increasing and the type is varied such as peer-to-peer (PZP), real-time video, and so on, because distributed computing environment is spread and various network-based applications are developed. However, as PZP traffic occupies much volume among Internet backbone traffics, transmission bandwidth and quality of service(QoS) of other network applications such as web, ftp, and real-time video cannot be guaranteed. In previous research, the port-based technique which checks well-known port number and the Deep Packet Inspection(DPI) technique which checks the payload of packets were suggested for solving the problem of the P2P traffics, however there were difficulties to apply those methods to detection of P2P traffics because P2P applications are not used well-known port number and payload of packets may be encrypted. A proposed algorithm for identifying P2P heavy traffics based on flow transport parameters and behavioral characteristics can solve the problem of the port-based technique and the DPI technique. The focus of this paper is to identify P2P heavy traffic flows rather than all P2P traffics. P2P traffics are consist of two steps i)searching the opposite peer which have some contents ii) downloading the contents from one or more peers. We define P2P flow patterns on these P2P applications' features and then implement the system to classify P2P heavy traffics.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.4
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• pp.334-348
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• 2005

The goal of next generation digital broadcasting is offering the interaction among consumers and providers as well as variety services. One of the important factors for this new broadcasting environment keeps the interoperability among providers and consumers since the environment is distributed. Therefore a standard metadata for digital broadcasting is required and TV-Anytime metadata is one of the metadata standards for digital broadcasting. The terminal nodes of TV-Anytime metadata are defined by using MPEG-7 metadata. MPEG-7 metadata is standard metadata for describing multimedia content. Therefore, if we use the MPEG-7 metadata for describing broadcasting content can offer multimedia search services like content-based search by the extension of metadata. The efficient management system for these metadata is important for offering the services with high Duality on real broadcasting environment TV-Anytime metadata and MPEG-7 metadata are technically defined using a single XML schema, so its instances are XML data. Currently, a lot of systemsfor managing XML data are proposed in many researchers and we can expect to adapt these systems for managing broadcasting metadata. But the methods used in these systems are not specific methods for managing broadcasting metadata because of methods for general-purpose. In this paper, we find the properties of broadcasting metadata and develop an efficient metadata management system that is based on the found properties. Since our systemis implemented on real broadcasting environment, we expect that the system is most efficient and suitable. Also our system is interoperable since we use XQuery as query language for querying broadcasting metadata.

• Journal of the Korean Institute of Gas
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• v.22 no.6
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• pp.136-143
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• 2018

Cellular automata have been applied to simulations in many fields such as astrophysics, social phenomena, fire spread, and evacuation. Using cellular automata, this study develops a model for consequence analysis of the dispersion of hazardous chemicals, which is required for risk assessments of and emergency responses for frequent chemical accidents. Unlike in cases of detailed plant safety design, real-time accident responses require fast and iterative calculations to reduce the uncertainty of the distribution of damage within the affected area. EPA ALOHA and KORA of National Institute of Chemical Safety have been popular choices for these analyses. However, this study proposes an initiative to supplement the model and code continuously and is different in its development of free software, specialized for small and medium enterprises. Compared to the full-scale computational fluid dynamics (CFD), which requires large amounts of computation time, the relative accuracy loss is compromised, and the convenience of the general user is improved. Using Python open-source libraries as well as meteorological information linkage, it is made possible to expand and update the functions continuously. Users can easily obtain the results by simply inputting the layout of the plant and the materials used. Accuracy is verified against full-scale CFD simulations, and it will be distributed as open source software, supporting GPU-accelerated computing for fast computation.

• Journal of Korean Society of Archives and Records Management
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• v.19 no.3
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• pp.271-292
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• 2019

Recently, the central administrative agency changed its business management system to cloud-based On-nara 2.0. To transfer and manage the records of the cloud business management system, the National Archives Service has developed and distributed a cloud-based records management system. It serves as an opportunity to maximize the benefits of cloud computing and redesign the records management to be more effective and efficient. The process and method of electronic record management can be transformed through digital technologies. First, we can change the transfer method for electronic records. When the business and the records management systems share the same cloud storage, it is possible to transfer the content files between the two systems without moving the contents files physically, thus copying only the metadata and reducing the cost and the risk of integrity damage. Second, the strategy for allocating storage space for contents can be conceived. Assuming that the cloud storage is shared by the business and the record management systems, it is advantageous to distinguish the storage location based on the retention period of the content files. Third, systems that access content files, such as records creation, records management, and information disclosure systems, can share the cloud storage and minimize the duplication of content files.

• Convergence Security Journal
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• v.18 no.1
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• pp.19-31
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• 2018

As the ICT technologies advance, the unprecedently large amount of digital data is created, transferred, stored, and utilized in every industry. With the data scale extension and the applying technologies advancement, the new services emerging from the use of large scale data make our living more convenient and useful. But the cybercrimes such as data forgery and/or change of data generation time are also increasing. For the data security against the cybercrimes, the technology for data integrity and the time verification are necessary. Today, public key based signature technology is the most commonly used. But a lot of costly system resources and the additional infra to manage the certificates and keys for using it make it impractical to use in the large-scale data environment. In this research, a new and far less system resources consuming signature technology for large scale data, based on the Hash Function and Merkle tree, is introduced. An improved method for processing the distributed hash trees is also suggested to mitigate the disruptions by server failures. The prototype system was implemented, and its performance was evaluated. The results show that the technology can be effectively used in a variety of areas like cloud computing, IoT, big data, fin-tech, etc., which produce a large-scale data.

• Journal of the Korea Society for Simulation
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• v.30 no.4
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• pp.9-19
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• 2021

Electronic voting has been recognized as an alternative to complement the limitations of existing paper voting. At the same time, security concerns are being raised. This paper presents a blockchain-based electronic voting and survey system that can guarantee reliability. Our smart contract was created using Solidity on Ethereum which is a blockchain-based distributed computing platform, and the system was implemented in connection with the Javascript based user interface. In addition, in order to protect the personal information of participants, the system is generating hash of the personal data and storing the hash of users for the contract data. Since we exploited different kinds of languages for the system, we derived items of functionality testing and presented the functionality testing result. Moreover, we made use of the Chrome's performance evaluation functionality to see the response time of the blockchain-based system. In addition, we compared the performance with the system which has the same functionality on database. The contribution of this research is design and implementation of blockchain-based electronic voting system and presentation of the functionality and performance simulation result.