DOI QR코드

DOI QR Code

Fuzzy-based Dynamic Packet Scheduling Algorithm for Multimedia Cognitive Radios

멀티미디어 무선인지 시스템을 위한 퍼지 기반의 동적 패킷 스케줄링 알고리즘

  • Tung, Nguyen Thanh (School of Electrical Engineering, University of Ulsan) ;
  • Koo, In-Soo (School of Electrical Engineering, University of Ulsan)
  • Received : 2012.04.27
  • Accepted : 2012.06.08
  • Published : 2012.06.30

Abstract

Cognitive radio, a new paradigm for wireless communication, is being recently expected to support various types of multimedia traffics. To guarantee Quality of Service (QoS) from SUs, a static packet priority policy can be considered. However, this approach can easily satisfy Quality of Service of high priority application while that of lower priority applications is being degraded. In the paper, we propose a fuzzy-based dynamic packet scheduling algorithm to support multimedia traffics in which the dynamic packet scheduler modifies priorities of packets according to Fuzzy-rules with the information of priority and delay deadline of each packet, and determines which packet would be transmitted through the channel of the primary user in the next time slot in order to reduce packet loss rate. Our simulation result shows that packet loss rate can be improved through the proposed scheme when overall traffic load is not heavy.

무선 통신 시스템의 새로운 패러다임인 중의 하나인 무선 인지 시스템에서 다양한 종류의 멀티미디어 트래픽 지원이 예상된다. 2차 사용자들이 요구하는 서비스 품질을 만족하기 위하여, 패킷 우선권 기반의 정적 자원할당 기법이 고려될 수 있다. 하지만, 이 기법은 높은 우선권을 갖는 응용 서비스의 서비스 품질을 쉽게 만족시킬 수 있으나, 낮은 우선권을 갖는 응용 서비스의 서비스 품질은 저하될 수 있다. 이에 본 논문에서는 퍼지 이론 기반의 동적 패킷 스케줄링 알고리즘을 제안한다. 제안된 기법에서는 동적 패킷 스케줄러가 각 패킷의 우선권과 지연 마감 시간(delay deadline)을 입력으로 갖는 퍼지 규칙에 따라, 각 패킷의 우선권을 동적으로 변경하여 패킷 손실율을 최소화하는 관점에서 기 사용자 채널을 통해 다음 가용한 time slot에 어떤 2차 사용자가 데이터를 전송할 지를 결정한다. 시뮬레이션을 통해 제안된 알고리즘이 우선권 기반의 정적 자원할당기법 보다 패킷 손실율을 더 향상 시킬 수 있음을 보였다.

Keywords

References

  1. H.-P. Shiang and M. van der Schaar, "Queuing-based dynamic channel selection for heterogeneous multimedia applications over cognitive radio networks," IEEE Trans. Multimedia, vol. 10, no. 5, pp. 896-909, Aug. 2008. https://doi.org/10.1109/TMM.2008.922851
  2. Tigang Jiang, Honggang Wang, and Yan Zhang, "Modeling channel allocation for multimedia transmission over infrastructure based cognitive radio networks", IEEE Systems Journal, vol.5, no. 3, pp. 1932-8184, Sep. 2011.
  3. M. van der Schaar and F. Fu, "Spectrum access games and strategic learning in cognitive radio networks for delay-critical applications," Proc. IEEE, vol. 97, no. 4, pp. 720-740, Apr. 2009. https://doi.org/10.1109/JPROC.2009.2013036
  4. Yaxiao Zhao, Ming Song and Chungsheng Xin, "Delay Analysis for Cognitive Radio Networks Supporting Heterogenenous Traffic", 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, pp. 215-223, 2011.
  5. Hung Tran, Trung Q. Duong and Hans-Jurgen Zepernick, "Average waiting time of packets with different priorities in cognitive radio networks", Wireless Pervasive Computing (ISWPC), 5th IEEE International Symposium, pp. 122-127, 2010.
  6. Abdelaali Chaoub and Elhassane ibn-elhaj, "Markovian primary traffics in cognitive radio networks", International Conference on Electrical and Control Engineering (ICECE), pp. 5987 - 5991, 2011.
  7. Juliet Bates and Chris Gallon, Converged Multimedia Networks, John Wiley & Sons Ltd, 2006.

Cited by

  1. Traffic Anomaly Identification Using Multi-Class Support Vector Machine vol.14, pp.4, 2013, https://doi.org/10.5762/KAIS.2013.14.4.1942
  2. A Cooperative Spectrum Sensing Method based on Eigenvalue and Superposition for Cognitive Radio Networks vol.13, pp.4, 2013, https://doi.org/10.7236/JIIBC.2013.13.4.39