• KIISE Transactions on Computing Practices
• /
• v.22 no.2
• /
• pp.101-106
• /
• 2016

A femtocell network has been attracting attention as a promising solution for providing high data rate transmission over the conventional cellular network in an indoor environment. In this paper, we propose a distributed power control algorithm considering both indoor coverage and data load balancing in the femtocell network. As data traffic varies by time and location according to user distribution, each femto base station suffers from an unbalanced data load, which may degrade network performance. To distribute the data load, the base stations are required to adjust their transmission power dynamically. Since there are a number of base stations in practice, we propose a distributed power control algorithm. In addition, we propose the simple algorithm to detect the faulty base station and to recover coverage. We also explain how to insert a new base station into a deployed network. We present the simulation results to evaluate the proposed algorithms.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.11
• /
• pp.201-205
• /
• 1997

With the recent advance of Web and its associated technologies, information sharing on distribute computing environments has gained a great amount of attention from many researchers in many application areas, such as medicine, engineering, and business. One basic requirement of distributed medical consultation systems is that geographically dispersed, disparate participants are allowed to exchange information readily with each other. Such software also needs to be supported on a broad range of computer platforms to increase the software's accessibility. In this paper, the development of world-wide-web based medical consultation system or radiology imaging is addressed to provide the platform independence and great accessibility. The system supports sharing of 3-dimensional objects. We use VRML (Virtual Reality Modeling Language), which is the de-facto standard in 3-D modeling on the Web. 3-D objects are reconstructed from CT or MRI volume data using a VRML format, which can be viewed and manipulated easily in Web-browsers with a VRML plug-in. A Marching cubes method is used in the transformation of scanned volume data set to polygonal surfaces of VRML. A decimation algorithm is adopted to reduce the number of meshes in the resulting VRML file. 3-D volume data are often very large-sized, and hence loading the data on PC level computers requires a significant reduction of the size of the data, while minimizing the loss of the original shape information. This is also important to decrease network delays. A prototype system has been implemented (http://netopia.snu.ac.kr/-cyber/). and several sessions of experiments are carried out.

• Journal of Internet Computing and Services
• /
• v.20 no.6
• /
• pp.157-166
• /
• 2019

oneM2M has been adopted to national and global smart city platforms leveraging its benefits, oneM2M platform assures interoperability to devices and services with standard APIs. Existing access control mechanisms in the standard should be extended to easily distribute smart city data. Compared to the as-is standard, this paper proposes a new access control method with minimum human interventions during data distribution between data sellers and buyers. The proposal has been implemented as the new data marketplace APIs to oneM2M platform and used for data marketplace portal interworking. This also has been demonstrated with smart city PoC service.

• Journal of Internet Computing and Services
• /
• v.21 no.5
• /
• pp.39-48
• /
• 2020

Recently, the study and development of environment-friendly energy technique have increased in worldwide due to environmental pollution and energy resources problems. In vehicle industry, the development of electric vehicle(EV) is now on progress, and also, many other governments support the study and development and make an effort for EV to become widely available. In addition, though they strive to construct the EV infra such as a charge station for EV, the techniques related to managing charge demand and peak power are not enough. The standard of EV communication has been already established as ISO/IEC 15118, however, most of implemented EVs and EV charge stations do not support any communication between each of them. In this paper, an improved slow charge scheme for non-communication EVs is proposed and designed by using predicting charge demand. The proposed scheme consists of distributed charge model and charge demand prediction. The distributed charge model is designed to manage to distribute charge power depending on available charge power and charge demand. The charge demand prediction is designed to be used in the distributed charge model. The proposed scheme is based on the collected data which were from EV slow charge station in business building during the past 1 year. The system-level simulation results show that the waiting time of EV and the charge fee of the proposed scheme are better than those of the conventional scheme.

• KIISE Transactions on Computing Practices
• /
• v.22 no.1
• /
• pp.44-49
• /
• 2016

Recently, data has been growing dramatically along with the growth of social media and digital devices. A distributed memory processing system has been used to efficiently process large amounts of data. However, if a load is concentrated in a certain node in distributed environments, a node performance significantly degrades. In this paper, we propose a load balancing scheme to distribute load in a distributed memory environment. The proposed scheme replicates hot data to multiple nodes for managing a node's load and migrates the data by considering the load of the nodes when nodes are added or removed. The client reduces the number of accesses to the central server by directly accessing the data node through the metadata information of the hot data. In order to show the superiority of the proposed scheme, we compare it with the existing load balancing scheme through performance evaluation.

• Journal of Convergence for Information Technology
• /
• v.7 no.5
• /
• pp.177-182
• /
• 2017

As major ICT technologies such as IoT, cloud computing, and Big Data are being applied to manufacturing, smart factories are beginning to be built. The key of smart factory implementation is the ability to acquire and analyze data of the factory. Therefore, the need for a big data analysis platform is increasing. The purpose of this study is to construct a platform for big data analysis of manufacturing process and propose integrated method for analysis. The proposed platform is a RHadoop-based structure that integrates analysis tool R and Hadoop to distribute a large amount of datasets. It can store and analyze big data collected in the unit process and factory in the automation system directly in HBase, and it has overcome the limitations of RDB - based analysis. Such a platform should be developed in consideration of the unit process suitability for smart factories, and it is expected to be a guide to building IoT platforms for SMEs that intend to introduce smart factories into the manufacturing process.

• Journal of Internet Computing and Services
• /
• v.20 no.5
• /
• pp.121-132
• /
• 2019

As the 4th industrial age enters, the number of IoT devices is exploding. Accordingly, the importance of security is also increasing in proportion to the increasing number of security incidents of IoT devices. However, due to the limited performance of IoT devices, there are limitations to applying existing security solutions. Therefore, a new automatic firmware distribution solution is needed to solve this problem. To solve this problem, we propose a new automatic firmware update system that uses a hybrid blockchain that combines a public blockchain and a private blockchain. The public blockchain allows various firmware providers to distribute firmware using a common system. Private blockchain solves the transaction overload problem of the public blockchain and facilitates the management of IoT devices. It also uses distributed file storage to ensure high availability without failing. Therefore, this system is expected to be very effective for improving the security of IoT devices.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.31 no.3
• /
• pp.517-526
• /
• 2021

Recently, the acceleration of the development of quantum computers has raised the issue of the safety of factorization and discrete logarithm based digital signature schemes used in existing Internet environments. To solve the issue, several digital signature schemes are presented that are safe in post-quantum computing environments, including standardization work by the National Institute of Standards and Technology(NIST). In this paper, we design and present a multi-signature scheme based on the TACHYON announced by Behnia et al. in 2018 CCS conference, and prove the security. Multi-signature schemes are key techniques that can distribute the dependence of cryptocurrency-wallet on private keys in the cryptocurrency field, which has recently received much attention as an digital signature application, and many researchers and developers have recently been interested. The multi-signature scheme presented in this paper enables public key aggregation in a plain public key model, which does not require additional zero-knowledge proof, and can construct an effective scheme with only an aggregated public key.

• Journal of Fashion Business
• /
• v.26 no.1
• /
• pp.1-15
• /
• 2022

Digital transformation has induced changes in human life patterns; consumption patterns are also changing to digitalization. Entering the era of industry 4.0 with the 4th industrial revolution, it is important to pay attention to a new paradigm in the fashion industry, the shift from developer-centered to user-centered in the era of the 3rd industrial revolution. The meaning of storing users' changing life and consumption patterns and analyzing stored big data are linked to consumer sentiment. It is more valuable to read emotions, then develop and distribute products based on them, rather than developer-centered processes that previously started in the fashion market. An AI(Artificial Intelligence) deep learning algorithm that analyzes user emotion big data from user experience(UX) to emotion and uses the analyzed data as a source has become possible. By combining AI technology, the fashion industry can develop various new products and technologies that meet the functional and emotional aspects required by consumers and expect a sustainable user experience structure. This study analyzes clear and useful user experience in the fashion industry to derive the characteristics of AI algorithms that combine emotions and technologies reflecting users' needs and proposes methods that can be used in the fashion industry. The purpose of the study is to utilize information analysis using big data and AI algorithms so that structures that can interact with users and developers can lead to a sustainable ecosystem. Ultimately, it is meaningful to identify the direction of the optimized fashion industry through user experienced emotional fashion technology algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.12
• /
• pp.1800-1808
• /
• 2022

During the election period, many polling agencies survey and distribute the approval ratings for each candidate. In the past, public opinion was expressed through the Internet, mobile SNS, or community, although in the past, people had no choice but to survey the approval rating by relying on opinion polls. Therefore, if the public opinion expressed on the Internet is understood through natural language analysis, it is possible to determine the candidate's approval rate as accurately as the result of the opinion poll. Therefore, this paper proposes a method of inferring the approval rate of candidates during the election period by synthesizing the political comments of users through internet community posting data. In order to analyze the approval rate in the post, I would like to suggest a method for generating the model that has the highest correlation with the actual opinion poll by using the KoBert, KcBert, and KoELECTRA models.