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IoT 환경에서 네트워크 대역폭을 고려한 스무딩 알고리즘의 성능 평가

Performance Evaluation of Smoothing Algorithm Considering Network Bandwidth in IoT Environment

  • 이면재 (백석대학교 컴퓨터공학부)
  • Lee, MyounJae (Division of Computer Engineering, BaekSeok University)
  • 투고 : 2022.05.16
  • 심사 : 2022.07.04
  • 발행 : 2022.08.31

초록

스무딩은 가변 비트율로 저장된 비디오 데이터를 고정 비트율로 변환하는 전송 계획이다. 스무딩을 위한 알고리즘에는 전송률 증가횟수의 최소화를 목적으로 하는 CBA, 전송률 변화 횟수를 최소화하는 MCBA, 전송률 변화량을 최소화하는 MVBA 알고리즘등이 있다. 본 연구는 서버에서 보다 많은 대역폭을 확보하기 위해 전송률 증가(감소)가 요구되는 경우에는 전송률 증가량(감소량)을 최소화(최대화)하는 스무딩 알고리즘을 제안한 연구의 후속 연구로 다양한 비디오 데이터와 버퍼크기, 성능 평가 요소로 제안 알고리즘을 CBA 알고리즘과 비교 분석한다. 사용된 평가요소는 재생률 변화 횟수, 최소 재생률, 평균 재생률, 재생률 변화량, 폐기되는 프레임 갯수로 비교하였다. 비교 결과, 제안 알고리즘은 재생률 변화 횟수와 폐기되는 프레임 개수 비교에서 우수함을 보였다.

Smoothing is a transmission plan that converts video data stored at a variable bit rate into a fixed bit rate. Algorithms for smoothing include CBA, which aims to minimize the number of transmission rate increases, MCBA, which minimizes the number of transmission rate changes, and MVBA algorithms that minimize the amount of transmission rate change. This paper compares the proposed algorithm with the CBA algorithm with various video data, buffer size, and performance evaluation factors as a follow-up to the proposed smoothing algorithm that minimizes (maximizes) the transmission rate increase (decrease) when the server requires more bandwidth The evaluation factors used were compared with the number of changes in the fps rate, the minimum fps, the average fps, fps variability, and the number of frames to be discarded. As a result of the comparison, the proposed algorithm showed superiority in comparing the number of fps rate changes and the number of frames discarded.

키워드

과제정보

본 논문은 2022학년도 백석대학교 학술연구비 지원을 받아 작성되었음

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