• Title/Summary/Keyword: streaming data

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Design and Implementation of a Network-Adaptive Mechanism for HTTP Video Streaming

  • Kim, Yo-Han;Shin, Jitae;Park, Jiho
    • ETRI Journal
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    • v.35 no.1
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    • pp.27-34
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    • 2013
  • This paper proposes a network-adaptive mechanism for HTTP-based video streaming over wireless/mobile networks. To provide adaptive video streaming over wireless/mobile networks, the proposed mechanism consists of a throughput estimation scheme in the time-variant wireless network environment and a video rate selection algorithm used to increase the streaming quality. The adaptive video streaming system with proposed modules is implemented using an open source multimedia framework and is validated over emulated wireless/mobile networks. The emulator helps to model and emulate network conditions based on data collected from actual experiments. The experiment results show that the proposed mechanism provides higher video quality than the existing system provides and a rate of video streaming almost void of freezing.

Performance Evaluation Technique of the RTSP based Streaming Server (RTSP기반 스트리밍 서버의 성능 측정 기술)

  • Lee YongJu;Min OkGee;Kim HagYoung;Kim MyungJoon
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07a
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    • pp.799-801
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    • 2005
  • There have been many streaming servers that provide a large number of contents for a user's preference. General purpose streaming sewer makes use of a RTSP protocol for streaming controls such as message passing with client players. To date, there has been minimal research regarding streaming server's performance test tools. For measuring streaming server's performance, performance evaluation technique is needed and also achieved by RTSP based controls, a server's performance result and its miscellaneous test tools such the PseudoPlayer for pumping data to a specified port and the PseudoMonitor for gathering information. In this paper, We implement a test toolkit for evaluating a streaming server's performance and show the case of its application

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Research of Knowledge Management and Reusability in Streaming Big Data with Privacy Policy through Actionable Analytics (스트리밍 빅데이터의 프라이버시 보호 동반 실용적 분석을 통한 지식 활용과 재사용 연구)

  • Paik, Juryon;Lee, Youngsook
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.12 no.3
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    • pp.1-9
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    • 2016
  • The current meaning of "Big Data" refers to all the techniques for value eduction and actionable analytics as well management tools. Particularly, with the advances of wireless sensor networks, they yield diverse patterns of digital records. The records are mostly semi-structured and unstructured data which are usually beyond of capabilities of the management tools. Such data are rapidly growing due to their complex data structures. The complex type effectively supports data exchangeability and heterogeneity and that is the main reason their volumes are getting bigger in the sensor networks. However, there are many errors and problems in applications because the managing solutions for the complex data model are rarely presented in current big data environments. To solve such problems and show our differentiation, we aim to provide the solution of actionable analytics and semantic reusability in the sensor web based streaming big data with new data structure, and to empower the competitiveness.

Design and Implementation of the Ensemble-based Classification Model by Using k-means Clustering

  • Song, Sung-Yeol;Khil, A-Ra
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.10
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    • pp.31-38
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    • 2015
  • In this paper, we propose the ensemble-based classification model which extracts just new data patterns from the streaming-data by using clustering and generates new classification models to be added to the ensemble in order to reduce the number of data labeling while it keeps the accuracy of the existing system. The proposed technique performs clustering of similar patterned data from streaming data. It performs the data labeling to each cluster at the point when a certain amount of data has been gathered. The proposed technique applies the K-NN technique to the classification model unit in order to keep the accuracy of the existing system while it uses a small amount of data. The proposed technique is efficient as using about 3% less data comparing with the existing technique as shown the simulation results for benchmarks, thereby using clustering.

Applying Realtime Video/Audio streaming technology to Online service (Realtime Video/Audio Streaming 기술과 컴퓨터통신 서비스)

  • 이경한
    • Proceedings of the Korea Database Society Conference
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    • 1997.10a
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    • pp.319-334
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    • 1997
  • 불과 2년 전만 하더라도 인터넷에서 오디오 또는 비디오 데이터를 감상하기까지 일련의 과정은 그 데이터의 물리적인 양과 전달방식에 있어서 이용자들에게 많은 인내력을 요구해 왔다. 이에 대한 해결책으로 관련업계에서는 real-time streaming 기술을 도입하여 각종 비디오와 오디오 데이터 전송에 관련기술을 적용시킴으로서 실시간 비디오/오디오 서비스 이용을 용이하게 하려는 움직임이 활발히 진행되어 왔었다.(중략)

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The Study on the Development of the Realtime HD(High Definition) Level Video Streaming Transmitter Supporting the Multi-platform (다중 플랫폼 지원 실시간 HD급 영상 전송기 개발에 관한 연구)

  • Lee, JaeHee;Seo, ChangJin
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.65 no.4
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    • pp.326-334
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    • 2016
  • In this paper for developing and implementing the realtime HD level video streaming transmitter which is operated on the multi-platform in all network and client environment compared to the exist video live streaming transmitter. We design the realtime HD level video streaming transmitter supporting the multi-platform using the TMS320DM386 video processor of T.I company and then porting the Linux kernel 2.6.29 and implementing the RTSP(Real Time Streaming Protocol)/RTP(Real Time Transport Protocol), HLS(Http Live Streaming), RTMP(Real Time Messaging Protocol) that can support the multi-platform of video stream protocol of the received equipments (smart phone, tablet PC, notebook etc.). For proving the performance of developed video streaming transmitter, we make the testing environment for testing the performance of streaming transmitter using the notebook, iPad, android Phone, and then analysis the received video in the client displayer. In this paper, we suggest the developed the Realtime HD(High Definition) level Video Streaming transmitter performance data values higher than the exist products.

Just One More Episode: Exploring Consumer Motivations for Adoption of Streaming Services

  • Arun T M;Shaili Singh;Sher Jahan Khan;Manzoor Ul Akram;Chetna Chauhan
    • Asia pacific journal of information systems
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    • v.31 no.1
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    • pp.17-42
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    • 2021
  • This study examines the adoption of subscription-based video on demand (SVOD) streaming services among consumers. Primarily, we explore the moderating effect of the two models of streaming services, standalone streaming services and bundled streaming services, on the users' adoption. We employ the Unified Theory of Acceptance and Use of Technology (UTAUT2) model in this study. We utilize the data collected from 337 Indian respondents and find that all constructs of the UTAUT2 model act as motivators of adoption. Gender, age, and experience of the respondent also play a moderating role in the adoption of streaming services. We also find that providing bundled streaming service positively moderates price-value and hedonic motivation of adoption. The study is perhaps the first of its kind that aims to understand the motivations for adoption of SVOD services, particularly in the Indian context, which has the fastest-growing base of internet users in the world.

RDFS Rule based Parallel Reasoning Scheme for Large-Scale Streaming Sensor Data (대용량 스트리밍 센서데이터 환경에서 RDFS 규칙기반 병렬추론 기법)

  • Kwon, SoonHyun;Park, Youngtack
    • Journal of KIISE
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    • v.41 no.9
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    • pp.686-698
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    • 2014
  • Recently, large-scale streaming sensor data have emerged due to explosive supply of smart phones, diffusion of IoT and Cloud computing technology, and generalization of IoT devices. Also, researches on combination of semantic web technology are being actively pushed forward by increasing of requirements for creating new value of data through data sharing and mash-up in large-scale environments. However, we are faced with big issues due to large-scale and streaming data in the inference field for creating a new knowledge. For this reason, we propose the RDFS rule based parallel reasoning scheme to service by processing large-scale streaming sensor data with the semantic web technology. In the proposed scheme, we run in parallel each job of Rete network algorithm, the existing rule inference algorithm and sharing data using the HBase, a hadoop database, as a public storage. To achieve this, we implement our system and evaluate performance through the AWS data of the weather center as large-scale streaming sensor data.

Cross-layered Video Information Sharing Method and Selective Retransmission Technique for The Efficient Video Streaming Services (효율적인 영상 스트리밍 서비스를 위한 Cross-layer 영상 정보 공유 방법 및 선택적 재전송 기법)

  • Chung, Taewook;Chung, Chulho;Kim, Jaeseok
    • Journal of Korea Multimedia Society
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    • v.18 no.7
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    • pp.853-863
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    • 2015
  • In this paper, we proposed cross-layered approach of video codec and communication system for the efficient video streaming service. Conventional video streaming is served by divided system which consist of video codec layer and communication layer. Its disintegration causes the limitation of the performance of video streaming service. With the cross-layered design, each layer could share the information and the service is able to enhance the performance. And we proposed the selective retransmission method in communication system based on the cross-layered system that reflect the information of encoded video data. Selective retransmission method which consider the characteristics of video data improves the performance of video streaming services. We verified the proposed method with raw format full HD test sequence with H.264/AVC codec and MATLAB simulation. The simulation results show that the proposed method improves about 10% PSNR performance.

A Continuous Query Processing System for XML Stream Data (XML 스트림 데이터에 대한 연속 질의 처리 시스템)

  • Han Seungchul;Kang Hyunchul
    • The KIPS Transactions:PartD
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    • v.11D no.7 s.96
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    • pp.1375-1384
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    • 2004
  • Streaming data processing is an area of interest with much research under way. There has been increasing attention on the demands for efficient processing of streaming data produced in the application areas such as monitoring and sensor network. We have developed a continuous query processing system for streaming data and evaluated its performance in this paper. XML, the standard for data exchange on the web, is used as the model for the streaming data and the XQuery appended with a time interval is adopted as the query language for expressing con-tinuous queries. In the proposed system, the result is produced through background processing and materialized for reute in subsequent query processing. Through a detailed set of performance experiments, we shoed the effectiveness of the proposed system.