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Rate Control Scheme for Improving Quality of Experience in the CoAP-based Streaming Environment

CoAP 기반의 스트리밍 환경에서 사용자 체감품질 향상을 위한 전송량 조절 기법

  • 강현수 (광운대학교 전자통신공학과) ;
  • 박지우 (광운대학교 전자통신공학과) ;
  • 정광수 (광운대학교 전자통신공학과)
  • Received : 2017.08.03
  • Accepted : 2017.09.13
  • Published : 2017.12.15

Abstract

Recently, as the number of Internet of Things users has increased, IETF (Internet Engineering Task Force) has released the CoAP (Constrained Application Protocol). So Internet of Things have been researched actively. However, existing studies are difficult to adapt to streaming service due to low transmission rate that result from buffer underflow. In other words, one block is transmitted one block to client's one request according to the internet environment of limited resources. The proposed scheme adaptively adjusts the rate of CON(Confirmable) message among all messages for predicting the exact network condition. Based on this, the number of blocks is determined by using buffer occupancy rate and content download rate. Therefore it improves the quality of user experience by mitigating playback interruption. Experimental results show that the proposed scheme solves the buffer underflow problem in Internet of Things streaming environment by controlling transmission rate according to the network condition.

최근 사물인터넷 이용자수의 증가에 따라 IETF(Internet Engineering Task Force)에서 CoAP(Constrained Application Protocol) 표준을 발표하면서 활발한 연구가 진행되고 있다. 그러나 기존 연구들은 자원이 제한적인 사물인터넷 환경에 맞게 전송 단위인 블록을 한 개씩 전송하기 때문에, 낮은 전송량으로 인한 버퍼 언더플로우의 발생으로 스트리밍 서비스에 적용되기 어렵다. 제안하는 기법은 전체 메시지 중 CON(Confirmable) 메시지의 비율을 적응적으로 조절하여 정확한 네트워크 상황을 예측하고, 이를 기반으로 버퍼 점유율, 콘텐츠 다운로드율을 이용하여 블록의 개수를 결정한다. 따라서 버퍼 언더플로우에 의한 재생 끊김을 완화하여 사용자 체감품질을 향상시킨다. 실험 결과를 통하여 제안하는 기법이 네트워크 상황에 따른 전송량 조절로 인해 사물인터넷 스트리밍 환경에서 버퍼 언더플로우 문제를 해결함을 확인하였다.

Keywords

Acknowledgement

Grant : 사람-사물간 자율적 인터랙션을 위한 사람의 내/외재적 의도 인식 기술 개발

Supported by : 정보통신기술진흥센터

References

  1. C. C. Aggarwal, N. Ashish, and A. Sheth, "The Internet of Things: a Survey from the Data-Centric Perspective," Managing and Mining Sensor Data, Springer, pp. 383-428, 2013.
  2. C. Bormann, K. Hartke, and Z. Shelby, "The Constrained Application Protocol (CoAP)," RFC 7252, Jun. 2014.
  3. S. Alvi, A. Bilal, G. Shah, L. Atzori, and W. Mahmood, "Internet of Multimedia Things: Vision and Challenges," Ad Hoc Networks, Vol. 33, pp. 87-111, Oct. 2015. https://doi.org/10.1016/j.adhoc.2015.04.006
  4. A. Betzler, J. Isern, C. Gomez, I. Demirkol, and J. Paradells, "Experimental Evaluation of Congestion Control for CoAP Communications Without End-to-End Reliability," Ad Hoc Networks, Vol. 52, pp. 183-194, Mar. 2016. https://doi.org/10.1016/j.adhoc.2016.07.011
  5. G. Choi, D. Kim, and I. Yeom, "Efficient Streaming over CoAP," Proc. of International Conference on IEEE Information Networking (ICOIN), pp. 476-478, Jan. 2016.
  6. S. Wei, and V. Swaminathan, "Low Latency Live Video Streaming over HTTP 2.0," Proc. of the ACM Workshop on Network and Operating System Support on Digital Audio and Video, Vol. 14, pp. 37-42, Mar. 2014.
  7. C. Borman, A. Betzler, C. Gomez, and I. Demirkol, "CoAP Simple Congestion Control/Advanced," IETF Internet Draft, Oct. 2016.
  8. V. Paxson, M. Allman, J. Chu, and M. Sargent, "Computing TCP's Retransmission Timer," RFC 6298, Jun. 2011.
  9. P. Karn, and C. Partridge, “Improving Round-Trip Time Estimates in Reliable Transport Protocols,” ACM Transactions on Computer Systems (TOCS), Vol. 9, No. 4, pp. 364-373, Nov. 1991. https://doi.org/10.1145/118544.118549
  10. A. Betzler, C. Gomez, I. Demirkol, and J. Paradells, "CoCoA+: An Advanced Congestion Control Mechanism for CoAP," Ad Hoc Networks, Vol. 33, pp. 126-139, Oct. 2015. https://doi.org/10.1016/j.adhoc.2015.04.007
  11. R. Huysegems, J. Van der hooft, T. Bostoen, P. Rodao alface, S. Petrangeli, T. Wauters, and F. De turck, "HTTP/2-Based Methods to Improve the Live Experience of Adaptive Streaming," Proc. of the ACM International Conference on Multimedia Computing, pp. 541-550, Oct. 2015.