• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1151-1161
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• 1998

In this paper, we are considering a heterogeneous processor system in which each processor may have different performance and reliability characteristics. In other to fully utilize this diversity of processing power it is advantageous to assign the program modules of a distributed program to the processors in such a way that the execution time of the entire program is minimized. This assignment of tasks to processors to maximize performance is commonly called load balancing, since the overloaded processors can perform their own processing with the performance degradation. For the task assignment problem, we propose a new objective function which formulates this imbalancing cost. Thus the task assignment problem is to be carried out so that each module is assigned to a processor whose capabilities are most appropriate for the module, and the total cost is minimized that sum of inter-processor communication cost and execution cost and imbalance cost of the assignment. To find optimal assignment is known to be NP-hard, and thus we proposed an efficient heuristic algorithm with time complexity $O(n^2m)$ in case of m task modules and n processors.

• Journal of the Korea Fashion and Costume Design Association
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• v.17 no.2
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• pp.111-124
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• 2015

This study inferred the symbolism of shaman's costume in China from shamanism and types of shaman's costume in Naje, Deokgang-hyun, Guiju-seong, China through field survey. Shamanism in China has complicated aspects due to negotiations with other culture for a long time while maintaining its own consistency based on ethnicity. Symbolism of shaman's costume in Naje, Guiju-seong, China is observed as follows. First, the shaman's costume in China appears differently from every Jangcha in relation to the position of god appearing in Jangcha when Tolosa takes the position of god as a symbol of sex and god. In Naje of China, the most important shaman's costume indicating the position of god has a unique mask for every deity. It communicates that Tolosa wearing a costume appropriate for the god of wine shall become the god in that Jangcha. Second, the shaman's costume in China has something to do with Yin-Yang and the five elements theory of Taoism as a symbol of shamanism visio of the universe and system of reason. Most of Tolosas hosting Naje are men but dress up as women by wearing Nagun looking like a skirt. Nagun is usually red, the color of Yang, which symbolizes that by wearing such costume that takes color of Yang, Tolosa expels an ominous thing by balancing yin and yang and taking god's strong power. Third, Tolosa takes an eight-breadth Nagun, as a symbol of people. An eight-breadth worn by Tolosa in Naje strengthens the spirit of union and fight of the Tujia nationality who live in Deokgang-hyun, Guiju-seong through folk legends. In this course, a symbolic meaning of the national spirit has been provided on an eight-breadth Nagun, a shaman's costume.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3066-3079
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• 2016

Recent years have witnessed a dramatic increase in topology research of wireless sensor networks (WSNs) where both energy consumption and survivability need careful consideration. To balance energy consumption and ensure survivability against both random failures and deliberate attacks, we resort to complex network theory and propose an energy-aware preferential attachment (EPA) model to generate a robust topology for WSNs. In the proposed model, by taking the transmission range and energy consumption of the sensor nodes into account, we combine the characters of Erdős -Rényi (ER) model and Barabasi-Albert (BA) model in this new model and introduce tunable coefficients for balancing connectivity, energy consumption, and survivability. The correctness of our theoretic analysis is verified by simulation results. We find that the topology of WSNs built by EPA model is asymptotically power-law and can have different characters in connectivity, energy consumption, and survivability by using different coefficients. This model can significantly improve energy efficiency as well as enhance network survivability by changing coefficients according to the requirement of the real environment where WSNs deployed and therefore lead to a crucial improvement of network performance.

• The Journal of Korean Physical Therapy
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• v.24 no.4
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• pp.268-275
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• 2012

Purpose: This study is to identify how eye movement influences the static balance and fall efficacy of the elderly who have experienced fall-related injuries. Methods: Thirty nine elderly who scored 24 points in the Korean mini mental state examination, were able to walk, and had no specific disease, were selected as the research subjects among elderly who have experienced fall-related injury more than once in the past year. Thus, 20 for the experimental group, and 19 for the control group were selected as subjects. The experiment was conducted for 6 weeks, including periods of evaluation before and after intervention. Results: The results with respect to the dependent variables are as follows: Substitute sample t-testing showed significant differences between each group in eye movement to check difference in balance performance and fall efficacy. When independent sample t-tests were conducted to compare static balancing performance and fall efficacy between the two groups after intervention, they showed significant differences in statistical terms (p<0.05). Conclusion: From the above results of the study, it was found that the application of eye movement combined with diverse fall prevention programs is effective, when enhancing static balance performance power and improving fall efficacy.

• Journal of Energy Engineering
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• v.28 no.4
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• pp.76-81
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• 2019

This paper is a review of the certification system required for various energy prosumer business models, including P2P energy trading and participation in small demand response programs, which are based on reliable production and consumption certification. One of the most important parameter in energy trading is ensuring the reliability of trading account balancing. Therefore, we studied to use big data pattern analysis based blockchain smart contract between trading partners to make its tradings are more reliable. For this purpose big data analysis system collected from the IoT AMI and a production authentication system using a private blockchain network linked with the AMI is discussed, using the blockchain smart contract are also suggested. Futhermore, energy trading system concept and business models are introduced.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.5
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• pp.280-292
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• 2014

Recently, heterogeneous networks consisting of small-cells on top of traditional macro-cellular network has attracted much attention, because traditional macro-cellular network is not suitable to support more demanding mobile data traffic due to its limitation of spatial reuse. However, due to the transmit power difference between macro- and small-cells, most users are associated with macro-cells rather than small-cells. To solve this problem, enhanced inter-cell interference coordination (eICIC) has been introduced. Particularly, in eICIC, the small-cell coverage is forcibly expanded to associate more users with small-cells. Then, to avoid cross-tier interference from macro-cells, these users are allowed to receive the data during almost blank subframe (ABS) in which macro-cells almost remain silent. However, this approach is not sufficient to balance the load between macro- and small-cells because it only expands the small-cell coverage. In this paper, we propose a load balance scheme improving proportional fairness for heterogeneous networks employing eICIC. In particular, the proposed scheme combines the greedy-based user association and the ABS rate determination in a recursive manner to perform the load balance.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.2
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• pp.71-81
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• 2021

This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.49-56
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• 2023

Machine learning methods diversely applied to the Internet of Things (IoT) field have been successful due to the enhancement of computer processing power. They offer an effective way of detecting malicious intrusions in IoT because of their high-level feature extraction capabilities. In this paper, we proposed a novel feature selection method for malicious intrusion detection in IoT by using an evolutionary technique - Genetic Algorithm (GA) and Machine Learning (ML) algorithms. The proposed model is performing the classification of BoT-IoT dataset to evaluate its quality through the training and testing with classifiers. The data is reduced and several preprocessing steps are applied such as: unnecessary information removal, null value checking, label encoding, standard scaling and data balancing. GA has applied over the preprocessed data, to select the most relevant features and maintain model optimization. The selected features from GA are given to ML classifiers such as Logistic Regression (LR) and Support Vector Machine (SVM) and the results are evaluated using performance evaluation measures including recall, precision and f1-score. Two sets of experiments are conducted, and it is concluded that hyperparameter tuning has a significant consequence on the performance of both ML classifiers. Overall, SVM still remained the best model in both cases and overall results increased.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.171-174
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• 2011

서버 클러스터에서 부하 분산기는 사용자의 요청을 각 서버로 분산시키는 역할을 한다. 리눅스 가상 서버(LVS: Linux Virtual Server)는 소프트웨어적으로 사용되는 부하 분산기로서 여러 가지 스케줄링 방식들을 가지고 있다. 그러나 부하 분산 시에 서버의 유동적인 부하 정보를 반영하지 못하는 단점이 있다. 이에 개선된 방식으로 서버의 동시 연결 개수에 따라 상한계(Upper Bound)와 하한계(Lower Bound)를 설정하고, 요청을 분산하는 동적 스케줄링(Dynamic Scheduling)이 존재한다. 그러나 서버의 상태에 따라 상한계와 하한계가 바뀔 수 있음에도 불구하고 이 값들이 고정되어 있다는 단점을 가진다. 본 논문에서는 기존 부하 분산 방법의 단점을 극복하는 서버 전력 정보에 기반한 스케줄링 방식을 제안한다. 제안된 방식은 서버의 부하 정보를 기반으로 에너지를 추정하고 전력 수치를 기반으로 LVS의 가중치 테이블을 주기적으로 갱신한다. 그리고 부하 분산기는 클라이언트로부터 요청 받은 트래픽을 각 서버의 에너지 소모 상태에 따라 적용시킴으로써 에너지 소모가 최소화되도록 부하를 분산한다. 또한 서버의 상태에 따라 상한계와 하한계가 바뀔수 있음을 고려하여 상한계와 하한계를 설정하지 않고 서버의 상태에 따라 적절하게 요청이 분배되도록 하였다. 15대의 PC를 사용하여 실험을 수행하였으며, 실험 결과는 기존 부하 분산 알고리즘 중 성능이 가장 좋은 알고리즘에 비해 서버의 성능이 동일한 경우 성능 및 소비전력 면에서 거의 동등하였고, 서버의 성능이 상이한 경우 50.2% 성능 향상 및 27.3% 소비 전력 절감을 확인하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.99-106
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• 2023

In this paper, we propose subregion-based area of interest management techniques for MMORPG(massively multiplayer online role playing games) integrating P2P(peer-to-peer) networking and cloud computing. For the crowded region, the proposed techniques partition it into several subregions and assign a player to manage each subregion as a coordinator. These techniques include a load balancing mechanism which regulates communication and computation overhead of such player below the specified threshold. We also provide a mechanism for satisfying the criterion, where subregions overlapped with each player's view must be switched quickly and seamlessly as the view moves around in the game world. In the proposed techniques where an efficient provisioning of resources is realized, they relieve a lot of computational power and network traffic, the load on the servers in the cloud by exploiting the capacity of the players effectively. Simulation results show that the MMORPG based on cloud and P2P architecture can reduce the considerable bandwidth at the server compared to the client server architecture as the available resources grow with the number of players in crowding or hotspots.