• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권7호
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• pp.2302-2324
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• 2014

Cluster-based wireless sensor network (WSN) can significantly reduce the energy consumption by data aggregation and has been widely used in WSN applications. However, due to the intrinsic many-to-one traffic pattern in WSN, the network lifetime is generally deteriorated by the unbalanced energy consumption in a cluster-based WSN. Therefore, energy efficiency and network lifetime improvement are two crucial and challenging issues in cluster-based WSNs. In this paper, we propose a Non-Uniform Node Distribution (NUND) scheme to improve the energy efficiency and network lifetime in cluster-based WSNs. Specifically, we first propose an analytic model to analyze the energy consumption and the network lifetime of the cluster-based WSNs. Based on the analysis results, we propose a node distribution algorithm to maximize the network lifetime with a fixed number of sensor nodes in cluster-based WSNs. Extensive simulations demonstrate that the theoretical analysis results determined by the proposed analytic model are consistent with the simulation results, and the NUND can significantly improve the energy efficiency and network lifetime.

• 한국정보통신학회논문지
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• 제27권1호
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• pp.124-130
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• 2023

본 논문에서는 K-평균 군집화 알고리즘을 사용하는 머신러닝을 활용하여 무선 센서 네트워크에서 센서 노드의 에너지 효율성을 향상시켜 네트워크의 수명을 향상시키고자 한다. 무선 센서 네트워크는 물리적인 센서로 배터리를 포함한 물리적 장치를 무선 네트워크로 구성한 것으로 센서 노드의 특성 상 에너지 소비를 최소화하여 네트워크 수 명을 최대화하기 위해 모든 자원을 효율적으로 사용해야 한다. 클러스터기반 접근 방식은 상대적으로 많은 수의 노 들로 구성된 그룹을 관리하는데 사용된다. 제안된 프로토콜에서는 기존의 LEACH 알고리즘을 개선하여 클러스터 기반 접근방식과 위치기반 접근 방식을 사용하여 클러스터 헤드를 선정하는 클러스터링 알고리즘을 제안한다. 개선 하고자 했던 성능 결과를 Matlab 시뮬레이션을 이용하여 측정하였다. 실험 결과를 통해 에너지 효율성 부분에 대해 K-means 클러스터링을 적용함으로써 에너지 효율이 개선되어 젠체 네트워크의 수명이 연장됨을 확인한다.

• 대기
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• 제15권1호
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• pp.35-46
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• 2005

Today, the outreach of National Meteorological Service such as PC cluster based Numerical Weather Prediction (NWP) technique is vigorous in the world wide. In this regard, WMO (World Meteorological Organization) asked KMA (Korea Meteorological Administration) to formulate a regional project, which cover most of RA II members, using similar technical system with KMA's. In that sense, Meteorological Research Institute (METRI) in KMA developed Mongolian NWP System (MNWPS) based on PC cluster and transferred the technology to Weather Service Center in Mongolia. The hybrid parallel algorithm and channel bonding technique were adopted to cut cost and showed 41% faster performance than single MPI (Message Passing Interface) approach. The cluster technique of Beowulf type was also adopted for convenient management and saving resources. The Linux based free operating system provide very cost effective solution for operating multi-nodes. Additionally, the GNU software provide many tools, utilities and applications for construction and management of a cluster. A flash flood event happened in Mongolia (2 September 2003) was selected for test run, and MNWPS successfully simulated the event with initial and boundary condition from Global Data Assimilation and Prediction System (GDAPS) of KMA. Now, the cluster based NWP System in Mongolia has been operated for local prediction around the region and provided various auxiliary charts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1884-1903
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• 2019

Device-to-Device (D2D) communications can provide proximity based services in the future 5G cellular networks. It allows short range communication in a limited area with the advantages of power saving, high data rate and traffic offloading. However, D2D communications may reuse the licensed channels with cellular communications and potentially result in critical interferences to nearby devices. To control the interference and improve network throughput in overlaid D2D cellular networks, a novel channel assignment approach is proposed in this paper. First, we characterize the performance of devices by using Poisson point process model. Then, we convert the throughput maximization problem into an optimal spectrum allocation problem with signal to interference plus noise ratio constraints and solve it, i.e., assigning appropriate fractions of channels to cellular communications and D2D communications. In order to mitigate the interferences between D2D devices, a cluster-based multi-channel assignment algorithm is proposed. The algorithm first cluster D2D communications into clusters to reduce the problem scale. After that, a multi-channel assignment algorithm is proposed to mitigate critical interferences among nearby devices for each D2D cluster individually. The simulation analysis conforms that the proposed algorithm can greatly increase system throughput.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제10권6호
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• pp.507-513
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• 2004

본 논문에서는 웹 클러스터 시스템의 효율적인 자원사용 방법에 관하여 연구하고자 한다. 시스템 자원, 즉 메모리 사용을 균형적으로 하는 엘 클러스터 시스템을 구현하기 위한 부하 분산 알고리즘을 제안하여 검토하고자 한다. 다양한 클러스터링 모델에서 반응시간을 성능 측정의 지수로 제시하였다. 또한 웹 클러스터 시스템의 동시사용자수를 기반으로 반응시간은 사용자 수론 증가시키면서 실험을 실시하였다. 제안된 알고리즘에 대한 모의실험 결과는 기존의 상용화된 알고리즘보다 좋은 결과를 보여주고 있다. 제안된 부하분산 알고리즘은 동시 사용자 수가 많은 시스템의 경우, 더 좋은 결과를 보여주고 있다. 제안된 알고리즘은 이기종으로 구성된 웹 서버 시스템에 유용할 것으로 사료된다.

• International Journal of Advanced Culture Technology
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• 제5권3호
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• pp.40-45
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• 2017

This data mining technique was used to extract useful information from percutaneous coronary intervention data obtained from the US public data homepage. The experiment was performed by extracting data on the area, frequency of operation, and the number of deaths. It led us to finding of meaningful correlations, patterns, and trends using various algorithms, pattern techniques, and statistical techniques. In this paper, information is obtained through efficient decision tree and cluster analysis in predicting the incidence of percutaneous coronary intervention and mortality. In the cluster analysis, EM algorithm was used to evaluate the suitability of the algorithm for each situation based on performance tests and verification of results. In the cluster analysis, the experimental data were classified using the EM algorithm, and we evaluated which models are more effective in comparing functions. Using data mining technique, it was identified which areas had effective treatment techniques and which areas were vulnerable, and we can predict the frequency and mortality of percutaneous coronary intervention for heart disease.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2006년도 가을 학술발표논문집 Vol.33 No.2 (B)
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• pp.233-237
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• 2006

This study proposes an innovative measure for evaluating the performance of text clustering. In using K-means algorithm and Kohonen Networks for text clustering, the number clusters is fixed initially by configuring it as their parameter, while in using single pass algorithm for text clustering, the number of clusters is not predictable. Using labeled documents, the result of text clustering using K-means algorithm or Kohonen Network is able to be evaluated by setting the number of clusters as the number of the given target categories, mapping each cluster to a target category, and using the evaluation measures of text. But in using single pass algorithm, if the number of clusters is different from the number of target categories, such measures are useless for evaluating the result of text clustering. This study proposes an evaluation measure of text clustering based on intra-cluster similarity and inter-cluster similarity, what is called CI (Clustering Index) in this article.

• 정보처리학회논문지A
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• 제13A권4호
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• pp.323-334
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• 2006

클러스터 파일 시스템의 성능을 결정짓는 주요 요소 중 하나는 메타 데이터 서비스의 성능이다. 본 논문에서는 메타 데이터 연산의 종류에 따라 적절한 메타 데이터 서버에게 클라이언트의 요청을 동적으로 분배할 수 있는 내용 기반의 부하 분산 알고리즘을 제안한다. 이 알고리즘에서는 메타 데이터 서버 사이에 데이터의 이동을 유발 시키는 대신 메타 데이터를 복제하고 수정 메시지를 로깅하게 함으로써, 기존의 알고리즘에 비해 클라이언트의 요청을 서버들에게 균등하게 분배하여 응답 지연 시간을 현저히 줄일 수 있었다.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1438-1444
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• 2018

Recently, with the development of Internet technologies and propagation of smart devices, use of microblogs such as Facebook, Twitter, and Instagram has been rapidly increasing. Many users check for new information on microblogs because the content on their timelines is continually updating. Therefore, clustering algorithms are necessary to arrange the content of microblogs by grouping them for a user who wants to get the newest information. However, microblogs have word limits, and it has there is not enough information to analyze for content clustering. In this paper, we propose a semantic-based K-means clustering algorithm that not only measures the similarity between the data represented as a vector space model, but also measures the semantic similarity between the data by exploiting the TagCluster for clustering. Through the experimental results on the RepLab2013 Twitter dataset, we show the effectiveness of the semantic-based K-means clustering algorithm.

• 한국인터넷방송통신학회논문지
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• 제15권3호
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• pp.155-161
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• 2015

무선 센서 네트워크에서 효율적인 에너지 소비는 매우 중요한 이슈이다. 해당 이슈에 대해서 최근 연구들에서는 클러스터 기반 라우팅 프로토콜들을 해법으로 제시하고 있다. 이러한 프로토콜에서는 클러스터 헤드의 에너지 고갈을 방지하기 위해 재클러스터링이 필요한데, 재클러스터링 과정에서 발생하는 오버헤드도 적지 않다. 지나치게 빈번한 재클러스터링으로 인한 오버헤드를 줄이기 위해서 본 연구에서는 클러스터 헤드와 에너지 임계값의 비교를 통해 재클러스터링의 빈도를 조절하는 알고리즘을 제안하였다. 클러스터 헤드가 에너지 임계값보다 높은 에너지 수준을 가지고 있을 경우 클러스터를 유지하여 재클러스터링으로 인한 오버헤드를 줄였고, 낮을 경우 재클러스터링을 하여, 클러스터 헤드의 수명을 최대한 연장하였다. 제안한 알고리즘을 시뮬레이션을 통해 평가하여 기존 알고리즘 대비 우수한 에너지 효율을 가지는 것을 확인하였다.