Journal of Internet of Things and Convergence (사물인터넷융복합논문지)

The Korea Internet of Things Society (한국사물인터넷학회)
권호 표지
DOI QR코드

DOI QR Code

Performance Evaluation of Smoothing Algorithm for Efficient Use of Network Resources in IoT environments

IoT 환경에서 네트워크 자원의 효율적인 사용을 위한 스무딩 알고리즘의 성능평가

  • Lee, MyounJae (Division of Computer Engineering, BaekSeok University)
  • 이면재 (백석대학교 컴퓨터공학부)
  • Received : 2021.05.02
  • Accepted : 2021.06.14
  • Published : 2021.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

In order to transmit video data stored in servers with limited bandwidth in IoT environments to many clients, a transmission plan must be established by considering factors such as the number of transmission rate changes, peak transmission rate, and transmission rate changes. This transmission plan is called smoothing, and includes CBA that minimizes the number of transmission rate increases, MCBA that minimizes the number of transmission rate changes, and MVBA to minimize the transmission rate changes. In this work, to evaluate the performance of the proposed algorithm[16], we compare the proposed algorithm with the existing smoothing algorithms with the peak rate, the number of transmission rate changes, the rate increase, the peak rate utilization, and the average transmission rate with various video data and buffer sizes. The evaluation results show that the proposed algorithm helps to efficiently use the server's finite network resources by establishing a transport plan with the lowest average transfer rate.

IoT(Internet of Things) 환경에서 한정된 대역폭을 갖는 서버에서 저장된 비디오 데이터를 많은 클라이언트들에게 전송하기 위해서는 전송률 변화 횟수, 첨두 전송률, 전송률 변화량 등의 요소를 고려하여 전송 계획을 세워야 한다. 이 전송 계획을 스무딩이라고 하며 전송률 증가 횟수를 최소화하는 CBA, 전송률 변화횟수를 최소화하는 MCBA, 전송률 변화량을 최소화하기 위한 MVBA 등이 있다. 본 연구에서는 평균 전송률을 최소화하기 위해 제안된 알고리즘[16]에 대한 성능을 평가하기 위해, 제안된 알고리즘과 기존 스무딩 알고리즘들에서의 첨두 전송률, 전송률 변화횟수, 전송률 증가횟수, 전송률 변화량, 첨두 전송률 이용률, 평균 전송률을 다양한 비디오 데이터와 버퍼 크기로 비교한다. 평가 결과 제안 알고리즘은 평균 전송률이 가장 낮은 전송 계획을 세움으로써, 서버의 한정된 네트워크 자원의 효율적인 사용에 도움을 준다.

Keywords

Acknowledgement

본 논문은 2021학년도 백석대학교 학술연구비 지원을 받아 작성되었음

References

  1. D. Le Gall, "MPEG: A video compression standard for multimedia applications", Communications of the ACM, Vol.34, April, pp.47-58, 1991. https://doi.org/10.1145/103085.103090
  2. W.Feng, "Rate-constrained bandwidth smoothing for the delivery of stored video", in SPIE Multimedia Networking and Computing, Vol.3020, pp.316-327, 1997.
  3. Ray-I chang,Meng-Chang Chen,Jan-Ming Ho and Ming-Tat Ko,"Schedulable Region for VBR Media Transmission with Optimal Resource Allocation and Utilization", infsci(1~2), pp.61-79, 2002.
  4. W.Feng, F.Jahanian, S.Sechrest, "An Optimal Bandwidth Allocation Strategy for the Delivery of Compressed Prerecoded Video", ACM/Springer-Verlag Multimedia Systems, Vol.5, No.5, pp.297-309, 1997. https://doi.org/10.1007/s005300050062
  5. MyounJae Lee, et,al, "An Efficient Smoothing Algorithm for Video Transmission at Variable Bit Rate", KIPS Transactions on Computer and Communication Systems, Vol.11, No.7, pp.1009-1022, 2004.
  6. W. Feng, S. Sechrest, "Critical Bandwidth Allocation for the Delivery of Compressed Prerecorded Video", Computer Communications, Vol.18, No.10, pp.709-717, 1995. https://doi.org/10.1016/0140-3664(95)98484-M
  7. W. Feng, et. al., "Smoothing and buffering for delivery of prerecorded compressed video", in Proc. of ISET/SPIE Symp. on Multimedia Comp. and Networking, pp.234-242, 1995.
  8. J. McManus and K.Ross, "Video on demand over ATM:Constant-rate Transmission and Transport", in proc.of ACM SIGMETRICS, pp.222-231, 1996.
  9. J. Zhang and J. Hui. "Applying traffic smoothing techniques for quality of service control in VBR video transmissions", Computer Communications, pp.375-389, 1998.
  10. J. Zhang and J. Y. Hui, "Traffic Characteristics and Smoothness Criteria in VBR Video Traffic Smoothing", in Proc. of the ICMC and Systems, Vol.1, pp.3-11. 1997,
  11. P. Thiran, et. al., "Network calculus applied to optimal multimedia smoothing", Proceedings IEEE INFOCOM 2001, pp.1474-1483, 2001.
  12. Han-Chieh Chao, C.L.Hung, "Efficient Changes and Variability Bandwidth Allocation for VBR Media Streams", IEEE International Conference on Communications. Conference Proceedings, Vol.12, pp. 179-185, 2001.
  13. J.D. Salehi, et. al., "Supporting stored video: Reducing rate variability and end-to-end resource requirements through optimal smoothing", in Proc. of ACM SIGMETRICS, pp.222-231, 1996.
  14. W. Feng and J. Rexford. "Performance evaluation of smoothing algorithms for transmitting prerecorded VBR video", IEEE Trans. on Multimedia, pp.302-312, 1999. https://doi.org/10.1109/TMM.2016.2614427
  15. Jae-Hwan Lim, Kee-Chun, Bang, "An Efficient Transmission Plan for Multimedia Data Transmission", Journal of Digital Contents Society, Vol.8, No.1, pp.9-15. 2007.
  16. MyounJae Lee, "Video Data Transfer Algorithms for Efficient Use of Network Bandwidth", Journal of Next-generation Convergence Information Services Technology, Vol.10, No.1, pp.11-20, 2021. https://doi.org/10.29056/jncist.2021.02.02