1. Analytical study of frame aggregation in error- prone channels 2014 YU-ANTL Lab Seminar May 29, 2014 Shinnazar Seytnazarov Advanced Networking Technology Lab. (YU-ANTL) Dept. of Information & Comm. Eng, Graduate School, Yeungnam University, KOREA (Tel : +82-53-810-3940; Fax : +82-53-810-4742 http://antl.yu.ac.kr/http://antl.yu.ac.kr/; E-mail : seytnazarovsho@ynu.ac.kr)

2. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 2 OUTLINE  Introduction  Overview of 802.11n MAC enhancements Frame Aggregation Block Acknowledgment  The analytical model Model assumptions Model description  Analytical results  Frame size dynamic adaptation  Conclusion  References

3. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 3 Introduction  Motivation Frame aggregation mechanism can increase the efficiency of MAC layer under ideal channel conditions However, under high Bit Error Rate (BER) sub-frame failures increases consequently can greatly affect the performance due to their retransmission cost So, there is a need to examine the effect of frame aggregation feature on the performance under different channel error conditions  Contribution of this paper Authors derive an analytical model to study the impact of the frame aggregation on the saturation throughput and access delay under lossy channels Based on numerical results, they propose an algorithm which can dynamically adjust the MPDU sub-frame size based on the maximum FER tolerable by frame's access category

4. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 4 Overview of 802.11n MAC enhancements: Frame Aggregation  Frame aggregation mechanisms  Block ACK

5. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 5 The analytical model  A. Model Assumptions To study the performance of frame aggregation under different channel conditions, we extend Bianchi’s model [4] to be suitable with 802.11n enhancements.4 Stations competing to access to the medium and operating in saturated conditions. Each station always has a traffic available for transmission. RTS/CTS access scheme Only A-MPDU aggregation

6. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 6 Model description

7. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 7 Model description (1)

8. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 8 Model description (2)

9. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 9 Model description (3)  1) The Saturation Throughput The network's saturation throughput is calculated as the ratio of the average number of bits being successfully transmitted in a time slot and the expected average length of a time slot Expected length of slot time: In the case of an RTS/CTS access mechanism (Fig. 2), they are determined as follows:Fig. 2

10. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 10 Model description (4)

11. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 11 Model description (5)

12. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 12 Analytical results (1)

13. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 13 Analytical results (2)

14. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 14 Analytical results (3)

15. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 15 Analytical results (4)

16. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 16 Frame size dynamic adaptation (1)  QoS requirements for some ACs according to paper VolP traffics are delay-sensitive and they should tolerate less than 1–2% packet loss with delays greater than 30ms Streaming video traffic is sensitive to the loss rate less than 5% and more tolerable to the delay where the latency should be no more than 4 to 5 seconds.  Station runs Algorithm 1 upon receiving Block ACK frame STA measures frame error rate (mFER) Then it can obtain bit error rate (mBER) After that, it compares the mFER with the maximum FER tolerable by the corresponding frame access category FERmax_AC

17. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 17 Frame size dynamic adaptation (2)

18. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 18 Frame size dynamic adaptation (3) If mFER ≥ FERmax_AC, STA has to use smaller frame aggregation size to meet the AC QoS requirements. Thus the subframe size is reduced using the following equation Else, it can increase the subframe size to enhance the throughput. However, the step size X_AC of this increase is variable corresponding to the access category parameters. For example we can not use large size for voice traffics. That's authors we have fixed a maximum subframe size for each AC (FSmax_AC).

19. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 19 Conclusion  In this paper Authors derived an analytical model capturing the effect of frame aggregation on the saturation throughput and the access delay under different channels conditions. The results showed that the network performance depends significantly on the sub-frame size. Authors designed an adaptive frame aggregation size algorithm.  In this algorithm, the MPDU subframe size is dynamically adjusted according to the measured FER value from the block acknowledgement frame.  In low FER channels, larger frame size is used to increase the throughput.  And in error-prone channels smaller frame aggregation size is used to meet applications QoS requirements.

20. Advanced Networking Tech. Lab. Yeungnam University (YU-ANTL) YU-ANTL Lab. Seminar Shinnazar Seytnazarov 20 References [1] IEEE 802.11n, Part 11: Standard for Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 5: Enhancements for Higher Throughput, Sept. 2009. [2] N. Wart, R. K. Sheshadri, W. Zheng, and D. Koutsonikolas, “A first look at 802.11n power consumption in smartphones,” in ACM Mobicom International Workshop on Practical Issues and Applications in Next Generation Wireless Networks (PINGEN), Istanbul, Turkey, Aug. 2012. [3] N. Hajlaoui, I. Jabri, M. Taieb, and M. Benjemaa, “A frame aggregation scheduler for qos-sensitive applications in IEEE 802.11n WLANs,” in International Conference onCommunications and Information Technology (ICCIT), Hammamet, Tunisia, June 2012. [4] G. Bianchi, “Performance analysis of the IEEE 802.11 distributed coordination function,” IEEE JSAC, vol. 18, no. 3, pp. 535– 547, Mar. 2000. [5] T. Li, Q. Ni, D. Malone, D. Leith, Y. Xiao, and R. Turletti, “Aggregation with fragment retransmission for very high-speed WLANs,” IEEE/ACM Transactions on Networking, vol. 17, no. 2, pp. 591–604, Apr. 2009. [6] E. Charfi, L. Chaari, and L. Kamoun, “Analytical analysis of applying aggregation with fragment retransmission on IEEE 802.11e EDCA network in saturated conditions,” in International Conference on Communications and Networking (ComNet), Hammamet, Tunisia, Apr. 2012. [7] S. Frohn, S. Gubner, and C. Lindemann, “Analyzing the effective throughput in multi-hop IEEE 802.11n networks,” Computer Communications, vol. 34, no. 16, pp. 1912–1921, Oct. 2011. [8] B. S. Kim, H. Y. Hwang, and D. K. Sung, “Effect of frame aggregation on the throughput performance of IEEE 802.11n,” in IEEE WCNC, Las Vegas, Nevada, USA, Apr. 2008, pp. 1740–1744. [9] R. Hoefel, “IEEE 802.11n MAC improvements: A MAC and PHY crosslayer model to estimate the throughput,” in IEEE VTC, Calgary, Alberta, Canada, Sept. 2008. [10] Y. Daldoul, T. Ahmed,, and D. Meddour, “Ieee 802.11n aggregation performance study for the multicast,” in Wireless Days’11, Niagara Falls, Ontario, Canada, Oct. 2011. [11] Y. Lin and V. W. S. Wong, “Frame aggregation and optimal frame size adaptation for ieee 802.11n WLANs,” in GLOBECOM, San Francisco, CA, USA, Nov. 2006. [12] W. J. F. Heereman, E. Tanghe, D. Plets, L. Verloock, and L. Martens, “Path loss model and prediction of range, power and throughput for 802.11n in large conference rooms,” AEU-International Journal Of Electronics And Communications, vol. 66, no. 7, pp. 561–568, 2012. [13] J. Yin, X. Wang,, and D. P. Agrawal, “Optimal packet size in errorprone channel for IEEE 802.11 distributed coordination function,” in IEEE WCNC, Atlanta, USA, Mar. 2004. [14] S. Choi, J. DelPrado, and S. Mangold, “IEEE 802.11e contention-based channel access (EDCF) performance evaluation,” in ICC, Anchorage, AL, USA, May 2003.