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IoT 환경에서 서버 대역폭과 네트워크 트래픽을 고려한 스무딩 알고리즘

Smoothing Algorithm Considering Server Bandwidth and Network Traffic in IoT Environments

  • 이면재 (백석대학교 컴퓨터공학부)
  • Lee, MyounJae (Division of Computer Engineering, BaekSeok University)
  • 투고 : 2022.01.09
  • 심사 : 2022.02.17
  • 발행 : 2022.02.28

초록

스무딩은 가변 비트율로 저장된 비디오 데이터를 고정 비트율로 변환하는 전송 계획이다. [6,7]의 연구에서는 전송률 증가가 요구되는 되는 경우에 증가량이 가장 적은 프레임을 새로운 전송률 구간의 시작 프레임으로 설정하고, 전송률 감소가 요구되는 경우에 감소량이 가장 큰 프레임을 새로운 구간의 시작 프레임으로 설정하는 스무딩 알고리즘을 제안하고 네트워크 트래픽이 고려되지 않는 환경에서 성능을 평가하였다. 본 논문에서는 [6,7]의 스무딩 알고리즘을 네트워크 트래픽을 고려한 환경에서 E.T 90 비디오 데이터로 512KB부터 32MB까지 최소 재생률, 평균 재생률, 재생률 변화량으로 적응적인 CBA 알고리즘과 성능을 평가한다. 비교 결과, [6,7]의 스무딩 알고리즘은 최소 재생률 비교에서 우수함을 보였다.

Smoothing is a transmission plan that converts video data stored at a variable bit rate into a constant bit rate. In the study of [6-7], when a data rate increase is required, the frame with the smallest increase is set as the start frame of the next transmission rate section, when a data tate decrease is required. the frame with the largest decrease is set as the start frame of the next transmission rate section, And the smoothing algorithm was proposed and performance was evaluated in an environment where network traffic is not considered. In this paper, the smoothing algorithm of [6-7] evaluates the adaptive CBA algorithm and performance with minimum frame rate, average frame rate, and frame rate variation from 512KB to 32MB with E.T 90 video data in an environment that considers network traffic. As a result of comparison, the smoothing algorithm of [6-7] showed superiority in the comparison of the minimum refresh rate.

키워드

과제정보

본 논문은 2022학년도 백석대학교 학술연구비 지원을 받아 작성되었음

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