• Journal of Information Processing Systems
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• 제18권6호
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• pp.729-740
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• 2022

Netflix, Amazon Prime, and YouTube are the most popular and fastest-growing streaming services globally. It is a matter of great interest for the streaming service providers to preview their service infrastructure and streaming strategy in order to provide new streaming services. Hence, the first part of the paper presents a detailed survey of the Content Distribution Network (CDN) and cloud infrastructure of these service providers. To understand the streaming strategy of these service providers, the second part of the paper deduces a common quality-of-service (QoS) model based on rebuffering time, bitrate, progressive download ratio, and standard deviation of the On-Off cycle. This model is then used to analyze and compare the streaming behaviors of these services. This study concluded that the streaming behaviors of all these services are similar as they all use Dynamic Adaptive Streaming over HTTP (DASH) on top of TCP. However, the amount of data that they download in the buffering state and steady-state vary, resulting in different progressive download ratios, rebuffering levels, and bitrates. The characteristics of their On-Off cycle are also different resulting in different QoS. Hence a thorough adaptive bit rate (ABR) analysis is presented in this paper. The streaming behaviors of these services are tested on different access network bandwidths, ranging from 75 kbps to 30 Mbps. The survey results indicate that Netflix QoS and streaming behavior are significantly consistent followed by Amazon Prime and YouTube. Our approach can be used to compare and contrast the streaming services' strategies and finetune their ABR and flow control mechanisms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권1호
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• pp.414-435
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• 2017

As network adaptive streaming technology becomes increasingly common, transport protocol also becomes important in guaranteeing the quality of multimedia streaming. At the same time, because of the appearance of high-quality video such as Ultra High Definition (UHD), preventing buffering as well as preserving high quality while deploying a streaming service becomes important. The Internet Engineering Task Force recently published Multipath TCP (MPTCP). MPTCP improves the maximum transmission rate by simultaneously transmitting data over different paths with multiple TCP subflows. However, MPTCP cannot preserve high quality, because the MPTCP subflows slowly increase the transmission rate, and upon detecting a packet loss, drastically halve the transmission rate. In this paper, we propose a new multipath congestion control scheme for high-quality multimedia streaming. The proposed scheme preserves high quality of video by adaptively adjusting the increasing parameter of subflows according to the network status. The proposed scheme also increases network efficiency by providing load balancing and stability, and by supporting fairness with single-flow congestion control schemes.

• 한국IT서비스학회지
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• 제18권4호
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• pp.115-134
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• 2019

The global music industry has been growing steadily every year. In particular, the proportion of music streaming services in the overall market are expanding. It shows same pattern in domestic market. Also, several companies are providing music streaming services competitively. It is clear that there is growing interest in effective operations of music streaming services. In this study, we examine the impact of customization and network effect on service quality and customer loyalty. We collect survey data and analyze relationships between latent variables using structural equations modeling. We find that customization and network effect of music streaming services positively affect service quality. However, the effect of customization on customer loyalty is not significant and there is a negative effect of network effect on customer loyalty. Finally, we find that service quality works as a mediator between customization and customer loyalty, and service quality also works as a mediator between network effect and customer loyalty.

• 아태비즈니스연구
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• 제15권1호
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• pp.15-31
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• 2024

Purpose - This study explores the causes behind the high rate of impulse purchases in live streaming e-commerce. Design/methodology/approach - The research model is empirically validated with survey data collected from 324 respondents in China, using the Partial Least Squares (PLS) methodology. Findings - We found that the interactivity and visibility of live streaming are key in creating para-social relationships and perceived presence, leading to customers' impulse purchases. Research implications or Originality - This study deepens the understanding of consumers' impulse purchases in live-streaming e-commerce, revealing that para-social relationships and perceived presence developed through real-time interactions can increase impulse buying. It also highlights the differences between relationship-oriented and task-oriented interactions in fostering customers' perceived presence and para-social relationships in live streaming.

• 한국지하수토양환경학회지:지하수토양환경
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• 제26권6호
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• pp.1-17
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• 2021

Self-potential (SP) surveys measure naturally occurring differences in electrical potential in the absence of artificial sources and have been applied to various fields since the first application in mineral explorations. Among various causes of SP occurrences, streaming potential is generated by the flow of groundwater, and makes SP surveys suitable for the exploration of groundwater table fluctuation, fractures, sinkholes and landslide occurrences. Recently, there has been many studies that applied SP surveys to monitor water leakage through dikes and embankments. In this review paper, we first review the characteristics and theoretical backgrounds of streaming potential in saturated or unsaturated porous media to introduce it in the embankment among various application field. After the review of the background theory, we review the past cases of field SP surveys on dikes and embankments and also the characteristics of field streaming potential data in the surveys. Further, by analyzing past studies of qualitative as well as quantitative interpretation of SP survey data, we show the possibility of quantitative interpretation of streaming potential data obtained on dikes and embankments. Consequently, it is hope that this review paper helps researches on SP surveys on dikes and embankments, and provides basis for interpretation methods of the SP data to identify leaked area and further leakage rate (or permeability).

• International Journal of Contents
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• 제14권1호
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• pp.28-33
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• 2018

In this paper, we design and implement a distributed, moving objects management system for processing locations and sensor data from smart black boxes. The proposed system is designed and implemented based on Apache Kafka, Apache Spark & Spark Streaming, Hbase, HDFS. Apache Kafka is used to collect the data from smart black boxes and queries from users. Received location data from smart black boxes and queries from users becomes input of Apache Spark Streaming. Apache Spark Streaming preprocesses the input data for indexing. Recent location data and indexes are stored in-memory managed by Apache Spark. Old data and indexes are flushed into HBase later. We perform experiments to show the throughput of the index manager. Finally, we describe the implementation detail in Scala function level.

• 정보과학회 논문지
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• 제45권1호
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• pp.69-75
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• 2018

시간에 따라 순차적으로 들어오는 스트리밍 데이터에서는 전체 데이터 셋을 한꺼번에 모두 이용하는 배치 학습에 기반한 차원축소 기법을 적용하기 어렵다. 따라서 스트리밍 데이터에 적용하기 위한 점층적 차원 감소 방법이 연구되어왔다. 이 논문에서는 최소제곱오차해를 통한 점층적 선형 판별 분석법을 제안한다. 제안 방법은 분산행렬을 직접 구하지 않고 새로 들어오는 샘플의 정보를 이용하여 차원 축소를 위한 사영 방향을 점층적으로 업데이트한다. 실험 결과는 이전에 제안된 점층적 차원축소 알고리즘과 비교하여 이 논문에서 제안한 방법이 더 효과적인 방법임을 입증한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.571-573
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• 2014

오늘날 QoS 기술의 일환의 하나인 스트리밍 서비스의 기술들이 이슈화 되고 있다. 하지만 현재의 스트리밍 서비스는 한가지 화질의 영상으로 제공되며, 버퍼링과 같은 기술적인 문제점이 존재한다. 본 논문에서는 전송되는 스트림 데이터의 무결성을 위한 TCP와 스트림 데이터의 빠른 전송을 위한 UDP를 활용, 적응적 듀얼 스트리밍 시스템을 설계한다. 본 시스템에서는 실시간으로 들어오는 영상을 인코딩 과정을 통해 H.264기반의 여러 비트율의 영상을 바탕으로 서버와 클라이언트 간 TCP와 UDP를 통해 적응적인 네트워크 환경에서의 스트리밍 서비스를 제공한다. 이는 불특정 다수의 네트워크 환경에서 버퍼링의 최소화를 통해 지속적인 영상의 재생을 위한 다양한 스트리밍 분야와 멀티미디어 분야에 활용될 것이다.

• 정보과학회 논문지
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• 제43권6호
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• pp.718-723
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• 2016

스트리밍 데이터 분석에서 개념 변화가 일어나는 시점을 정확히 탐지하는 것은 분류 모델의 성능을 유지하는 데 있어서 매우 중요한 작업이다. 오류율은 스트리밍 데이터에서 개념 변화 탐지를 위해 많이 사용되는 척도이다. 그러나 0과 1로 이루어진 이진 값만으로 예측 결과를 묘사하는 것은 분류 모델의 행동 패턴을 나타내는 유용한 정보의 손실을 초래할 수 있다. 이 논문에서는 오류율을 이용하는 대신에 확률 예측치를 사용하여 분류기의 성능 패턴을 묘사하고 급격한 변화를 탐지하는 효과적인 개념 변화 탐지 방법을 제안한다. 합성데이터와 실제 스트리밍 데이터를 이용한 실험 결과는 제안한 방법이 개념 변화 시점을 탐지하는데 뛰어난 성능을 가짐을 보여준다.

• 한국정보통신학회논문지
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• 제12권4호
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• pp.677-684
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• 2008

원격지로부터 원격 실험을 수행하는데 있어서 수행된 실험 결과 데이터를 저장하고 재사용하여 실험을 재연하는 그리드 기반의 연구 시스템을 제안한다. 제안된 시스템은 Korea Construction Engineering Development (KOCED) 프로젝트에서 구축중인 실시간 하이브리드 실험 시설을 모델로 하여 설계되었다. 다양한 데이터를 사용자에게 제공하기 위하여, 실험 결과 데이터는 Publish/Subscribe 기반의 분산된 스트리밍 서버를 이용하여 관리되었다. 본 프로젝트의 데이터 특성을 고려하면서, 하나의 스트리밍 서버를 사용한 경우와 여러 개의 분산된 스트리밍 서버들을 사용한 경우를 시뮬레이션 하여 성능을 비교 및 분석하였다.