• Communications for Statistical Applications and Methods
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• 제13권3호
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• pp.719-732
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• 2006

A set of clustering algorithms with proper weight on the formulation of distance which extend to mixed numeric and multiple binary values is presented. A simple matching and Jaccard coefficients are used to measure similarity between objects for multiple binary attributes. Similarities are converted to dissimilarities between i th and j th objects. The performance of clustering algorithms with balancing weight on different similarity measures is demonstrated. Our experiments show that clustering algorithms with application of proper weight give competitive recovery level when a set of data with mixed numeric and multiple binary attributes is clustered.

• JSTS:Journal of Semiconductor Technology and Science
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• 제7권4호
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• pp.235-240
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• 2007

A current-balancing segmented group-inverting transmitter is presented for multi-Gb/s single-ended parallel links. With an additional increase of 4 pins, 16-bit data is efficiently encoded to 20 pins to achieve the current balancing and eliminate the simultaneous switching noise. Since the proposed coding is a simple inversion-or-not transformation of pre-defined groups of binary data, it can be implemented with simplified logic circuits. The transmitter is designed with a $0.18{\mu}m$ CMOS technology, and simulated eye diagrams at 5Gb/s show dramatic improvements in signal integrity.

• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.73-80
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• 2023

The recent growth in the use of mobile devices has contributed to increased computing and storage requirements. Cloud computing has been used over the past decade to cater to computational and storage needs over the internet. However, the use of various mobile applications like Augmented Reality (AR), M2M Communications, V2X Communications, and the Internet of Things (IoT) led to the emergence of mobile cloud computing (MCC). All data from mobile devices is offloaded and computed on the cloud, removing all limitations incorporated with mobile devices. However, delays induced by the location of data centers led to the birth of edge computing technologies. In this paper, we discuss one of the edge computing technologies, i.e., cloudlet. Cloudlet brings the cloud close to the end-user leading to reduced delay and response time. An algorithm is proposed for scheduling tasks on cloudlet by considering VM's load. Simulation results indicate that the proposed algorithm provides 12% and 29% improvement over EMACS and QRR while balancing the load.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권7호
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• pp.2354-2370
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• 2015

The advantages of employing SCTP-based Concurrent Multipath Transfer (CMT) have been demonstrated to be very useful for data delivery over multi-homed wireless networks. However, there is still significant ongoing work addressing some remaining limitations and challenges. The most important concern when applying CMT to data delivery is related to handling packet reordering and buffer blocking. Another concern on this topic is that current sender-based CMT solutions seldom consider balancing the overhead and sharing the load between the sender and receiver. This paper proposes a novel Receiver-driven Cooperation-based Concurrent Multipath Transfer solution (CMT-Rev) with the following aims: (i) to balance overhead and share load between the sender and receiver, by moving some functions including congestion and flow control from the sender onto receiver; (ii) to mitigate the data reordering and buffer blocking problems, by using an adaptive receiver-cooperative path aggregation model, (iii) to adaptively transmit packets over multiple paths according to their receiver-inspired sending rate values, by employing a new receiver-aware data distribution scheduler. Simulation results show that CMT-Rev outperforms the existing CMT solutions in terms of data delivery performance.

• 대한교통학회지
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• 제20권4호
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• pp.63-72
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• 2002

본 연구는 교통수요 추정에 관련된 사회경제적 통계자료와 여러 기관에서 발표된 Data를 바탕으로 TCS OD의 통행특성을 반영한 전국 교통수요를 추정하였다. 추정된 교통수요의 신뢰성을 검증하기 위해 전국을 8개권역으로 구분하여 권역별로 통행량을 비교하였으며, 통계적인 오차분석 기법을 이용하여 관측교통량과 배정교통량의 차이를 비교하였다. 그리고 추정된 교통수요의 통행시간분포(TLFD)와 주요도시간 통행소요시간을 분석하여 2-D와 3-D기법으로 추정된 교통수요의 신뢰성을 검증하였다. 신뢰성분석 및 검증결과 본 연구에서의 상황하에서는 3-D기법이 2-D기법보다는 TCS OD의 통행특성 및 패턴을 잘 반영하는 것으로 분석되었지만, 3-D기법이 전적으로 우수하다라고 단언할 수는 없을 것 같다.

• 한국컴퓨터정보학회논문지
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• 제12권3호
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• pp.51-58
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• 2007

확장성에서 장점을 가지고 있는 비공유 병렬 프로세서 구조는 병렬 데이터베이스 시스템에서 많이 적용되고 있는 구조이다. 그러나 비공유 병렬 프로세서 구조는 데이터의 분포가 전체 프로세서에게 균일하게 분포되어 있지 않을 경우에는 일부 프로세서에게 부하가 집중되고 이로 인한 성능의 감소가 불가피하게 되는 단점이 있다. 특히 부하의 불균형 정도가 심한 경우에 조인 연산을 수행할 때 이런 성능 감소의 단점은 두드러진다. 본 논문은 비공유 병렬 프로세서 구조에서 부하의 불균형 정도가 심한 경우에도, 조인 연산을 실시하기 전에 부하 불균형을 고려함으로써 성능 감소를 최소화하고, 메모리의 대용량화를 이용하여 성능을 높인 조인 알고리즘을 제시한다. 또한 알고리즘의 성능 분석을 위한 분석 모델을 제시하며, 분석 모델을 통하여 데이터 불균형 문제를 해결하기 위한 다른 알고리즘과의 성능을 비교한다.

• 한국통신학회논문지
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• 제40권7호
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• pp.1457-1467
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• 2015

해양 통신을 위한 VHF 대역 데이터 통신 시스템(VHF Data Exchange System: VDES)은 송수신단의 종류에 따라 서로 다른 주파수 대역을 사용하도록 설계되어 있으며, 육상국으로부터 멀리 떨어진 선박국에게 육상국과 연결성을 보장하기 위해 제안된 ASO-TDMA (Ad-hoc Self-Organizing TDMA) MAC 프로토콜을 이용하여 다중-홉 통신을 수행하는 경우에 주파수 채널간 부하 불균형 문제가 발생한다. 본 논문에서는 이러한 주파수 채널간 부하 불균형 문제를 해결하기 위해 통계적 기하(stochastic geometry) 모델링을 도입한다. 이를 기반으로 동일 홉 영역에서의 공간적 자원 재사용률을 분석하고, 각 홉 영역 별로 최적의 자원 할당을 통해 채널간의 부하 불균형 문제를 해결하여 자원 활용도를 극대화하는 것을 보인다.

• 한국정보통신학회논문지
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• 제8권7호
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• pp.1524-1531
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• 2004

본 논문에서는 라운드 로빈 알고리즘을 적용한 부하균형기법을 보이고 있다. 이를 위하여 2개의 패키지(패킷 캡춰와 라운드로빈 테스트 패키지)를 구현하였으며, 이러한 구현 패키지 S/W에 의해 본 연구 실험의 가상연결구조(데이터 생성기, 가상서버, 서버1,2,3) 에서 발생하는 패킷의 량을 측정한 것으로 서버1,2,3으로 트래픽 분산여부를 파악할 수 있었으며, 구현된 라운드로빈 부하균형 모니터링 시스템의 기능으로는 데이터의 수신량, 패킷량 표현, 패킷량 그래프 표현, 라운드 로빈 테스트, 시스템 모니터링 기능이 있다. 실험결과는 들어오는 데이터의 크기가 많이 차이나지 않는 이상 라운드 로빈 알고리즘은 확실한 형태의 트래픽 분산을 가능하게 해주었다 그리고 일부분에서 오차가 심한 경우도 있지만 횟수를 거듭하고 테스트가 장기화 될수록 오차는 줄어들었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4642-4660
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• 2016

One major concern of applying Multipath TCP (MPTCP) to data delivery in heterogeneous wireless networks is that the utilization of asymmetric paths with diverse networking-related parameters may cause severe packet reordering and receive buffer blocking (RB²LOC). Although many efforts are devoting to addressing MPTCP's packet reordering problems, their sender-controlled solutions do not consider balancing overhead between an MPTCP sender and receiver, and their fully MPTCP mode cannot make MPTCP achieve a desired performance. This paper proposes a novel receiver-centric buffer blocking-aware data scheduling strategy for MPTCP (dubbed MPTCP-rec) necessitating the following aims: (1) alleviating MPTCP's packet reordering and RB²LOC problems, (2) improving the MPTCP performance, and (3) balancing load between the MPTCP sender and receiver. Simulation results show that the proposed MPTCP-rec solution outperforms the existing MPTCP solutions in terms of data delivery performance in heterogeneous wireless networks.

• Smart Structures and Systems
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• 제30권6호
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.