• Journal of information and communication convergence engineering
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• 제20권3호
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• pp.143-152
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• 2022

The ongoing adoption of 5G will increase the data traffic, throughput, multimedia services, and power consumption for future wireless applications and services, including sensor and mobile networks. Multipath fading on wireless channels also reduces the system performance and increases energy consumption. To address these issues, device-to-device (D2D) and cooperative communications have been proposed. In this study, we propose two inter-clustering models using the relay selection method to improve system performance and increase energy efficiency in cooperative D2D networks. We develop two inter-clustering models and present their respective algorithms. Subsequently, we run a computer simulation to evaluate each model's outage probability (OP) performance, throughput, and energy efficiency. The simulation results show that inter-clustering model II has the lowest OP, highest throughput, and highest energy efficiency compared with inter-clustering model I and the conventional inter-clustering-based multirelay method. These results demonstrate that inter-clustering model II is well-suited for use in 5G overlay D2D and cellular communications.

• 한국통신학회논문지
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• 제40권5호
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• pp.860-862
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• 2015

본 논문에서는 Inter-Cloud 환경에서 효율적인 사용자 인증 및 권한 인가를 위한 새로운 형태의 IAM 클러스터링 아키텍처를 제안한다. 제안하는 클러스터링 아키텍처는 사전 Access Agreement를 통하여 사용자가 자신이 등록되지 않은 어떤 서비스도 간단하게 이용할 수 있도록 인증 및 접근 권한을 제공한다. 본 논문에서는 IAM 클러스터링 아키텍처의 구성요소 및 인증 프로토콜을 설명한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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• pp.665-683
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• 2011

Wireless sensor networks (WSN) consist of a large amount of sensor nodes distributed in a certain region. Due to the limited battery power of a sensor node, lots of energy-efficient schemes have been studied. Clustering is primarily used for energy efficiency purpose. However, clustering in WSNs faces several unattained issues, such as ensuring connectivity and scheduling inter-cluster transmissions. In this paper, we propose a location-based spiral clustering (LBSC) algorithm for improving connectivity and avoiding inter-cluster collisions. It also provides reliable location aware routing paths from all cluster heads to a sink node during cluster formation. Proposed algorithm can simultaneously make clusters in four spiral directions from the center of sensor field by using the location information and residual energy level of neighbor sensor nodes. Three logical addresses are used for categorizing the clusters into four global groups and scheduling the intra- and inter-cluster transmission time for each cluster. We evaluated the performance with simulations and compared it with other algorithms.

• 산업경영시스템학회지
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• 제24권65호
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• pp.41-50
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• 2001

Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and intercluster similarity is minimized. The discovered clusters from clustering process are used to explain the characteristics of the data distribution. In this paper we propose a new methodology for clustering related transactions with categorical attributes. Our approach starts with transforming general relational databases into a transactional databases. We make use of inter-dimensional association rules for composing hypergraph edges, and a hypergraph partitioning algorithm for clustering the values of attributes. The clusters of the values of attributes are used to find the clusters of transactions. The suggested procedure can enhance the interpretation of resulting clusters with allocated attribute values.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권3호
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• pp.178-183
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• 2011

The deterministic annealing-based clustering algorithm is an EM-based algorithm which behaves like simulated annealing method, yet less sensitive to the initialization of parameters. Pairwise clustering is a kind of clustering technique to perform clustering with inter-entity distance information but not enforcing to have detailed attribute information. The pairwise deterministic annealing-based clustering algorithm repeatedly alternates the steps of estimation of mean-fields and the update of membership degrees of data objects to clusters until termination condition holds. Lacking of attribute value information, pairwise clustering algorithms do not explicitly determine the centroids or medoids of clusters in the course of clustering process or at the end of the process. This paper proposes a method to identify the medoids as the centers of formed clusters for the pairwise deterministic annealing-based clustering algorithm. Experimental results show that the proposed method locate meaningful medoids.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.998-1007
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• 2018

The advent of Wireless Sensor Networks (WSN) has led to their use in numerous applications. Sensors are autonomous in nature and are constrained by limited resources. Designing an autonomous topology with criteria for economic and energy conservation is considered a major goal in WSN. The proposed honey-hive clustering consumes minimum energy and resources with minimal transmission delay compared to the existing approaches. The honey-hive approach consists of two phases. The first phase is an Intra-Cluster Min-Max Discrepancy (ICMMD) analysis, which is based on the local honey-hive data gathering technique and the second phase is Inter-Cluster Frequency Matching (ICFM), which is based on the global optimal data aggregation. The proposed data aggregation mechanism increases the optimal connectivity range of the sensor node to a considerable degree for inter-cluster and intra-cluster coverage with an improved optimal energy conservation.

• 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.

• 전기전자학회논문지
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• 제11권4호
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• pp.165-170
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• 2007

무선 센서 네트워크에서 클러스터링 프로토콜의 목적은 각 센서 노드의 에너지 소모를 최소화하여 네트워크의 생존 시간을 최대화 하는 것이다. 그러나 기존의 클러스터링 프로토콜은 센서 노드, 클러스터 헤드와 싱크 노드 사이의 통신방법을 제외하고 주로 클러스터를 구성하는 것에만 초점을 맞추고 있다. 본 논문에서는 기존의 클러스터링 프로토콜에 다중경로 라우팅 알고리즘을 적용하고, MAC 계층과 네트워크 계층 간의 cross-layer 설계를 이용하여 에너지 효율적인 클러스터링 프로토콜을 제안한다. 여기에서 다중경로 정보는 싱크로부터의 경로 요구 패킷을 네트워크에 전파시킴으로서 설정되며 또한 다중경로에 대한 정보는 무선채널의 브로드캐스팅 특징과 결합하여 데이터의 전송 확률을 증가시킨다. 실험 결과에 의하면 제안한 프로토콜이 클러스터 헤드의 부하를 낮춤으로써 무선 센서 네트워크의 생존 시간을 늘려주고, 네트워크 크기의 증가에 따라 에너지 소비의 증가율이 다소 낮아지는 것을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1238-1259
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• 2019

Saving energy is a big challenge for Wireless Sensor Networks (WSNs), which becomes even more critical in large-scale WSNs. Most energy waste is communication related, such as collision, overhearing and idle listening, so the schedule-based access which can avoid these wastes is preferred for WSNs. On the other hand, clustering technique is considered as the most promising solution for topology management in WSNs. Hence, providing interference-free clustering is vital for WSNs, especially for large-scale WSNs. However, schedule management in cluster-based networks is never a trivial work, since it requires inter-cluster cooperation. In this paper, we propose a clustering method, called Interference-Free Clustering Protocol (IFCP), to partition a WSN into interference-free clusters, making timeslot management much easier to achieve. Moreover, we model the clustering problem as a multi-objective optimization issue and use non-dominated sorting genetic algorithm II to solve it. Our proposal is finally compared with two adaptive clustering methods, HEED-CSMA and HEED-BMA, demonstrating that it achieves the good performance in terms of delay, packet delivery ratio, and energy consumption.

• 품질경영학회지
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• 제24권1호
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• pp.126-136
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• 1996

In multi-item production system, GT(Group Technology) is used effectively in order to cluster various parts into groups. GT is based on clustering parts which have similar features, and these features are classified into two properties, namely crisp(quantitative) feature and fuzzy(qualitative) feature. Especially, many difficult problems are often faced that have to evaluate the properties of parts with the crisp and fuzzy feature together. As the basis of determining the similarity of inter-parts, in this method, one aggregate value is calculated on each part. However, because the above aggregate value is only gained from simple additive weighted sum, there is one problem in this method that has been handled the combination effect of inter-parts. For these reasons, in this paper, a proposed method is suggested for representing combination effect in order to cluster parts that have crisp and fuzzy properties into groups using ${\lambda}$-fuzzy measure and fuzzy integral.