Chapter 3 Fuzzy Call Admission Control (CAC) for WLAN Gateway in
3.4. A Gaussian Approximation for Equivalent CAP Estimator
For the fairness of real-time transmission, we take Round Robin scheduling method.
When the video packets arrives during the two successive superframes can not be transmitted during the following three superframes, these video are dropped by the QAP. We assume the
r bound
CAP could support the N users at a certain drop probability, and then we could formulate as follows:
where pdropis the bound we want to guarantee which is the drop bound of the real-time call. we assume the CAPi during the two successive superframes are independent and identically distributions. Then (3.10) could be written to (3.11)
2N r
we take a Gaussian approximation method for the summation of CAPi(n) as (3.12) and the mean (
µ
) and variance (σ
2) of the new real-time CAPi could be known by the QAP from the peak rate and mean rate of the new call. That is2N
We use the approximation table look method, so the N and CAPe could be derived.
r
In this chapter, for real-time service requesting calls, we proposed a fuzzy CAC algorithm at QAP for WLAN in SOHO/Home networks. The input linguistic variables we consider are used for checking the system load and whether satisfying the required QoS of the existed traffic in the system. We take a Gaussian approximation to the CAP estimator which is discussed in the 3.4. The QoS requirements are drop rates of real-time services, and loss rate of data downlink due to overflow at QAP. We have a procedure to design a fuzzy CAC algorithm for the wireless 802.11e MAC protocol and we consider the application real-time services including voice, video on-demand, and video conferencing.
Chapter 4 Conclusion
In this thesis, we first study the simulation phenomenon for 802.11e with hybrid services in chapter2. Three types of services are considered, ie. real-time voice, real-time video, and data services. For real-time service, the delay-considered drop is investigated and we find the data throughput is dynamical with the real-time service users. The difference priority in contention period guarantees the real-time service efficiently accessing the medium. We simulate the video traffic and to understand video throughput within the limit of the delay bound influenced by the voice pair number. We also modify the IFS of data which could enhance the medium efficiency under the hybrid contention traffics.
In chapter 3, we design a call admission control scheme in the SOHO/Home networks for WLAN gateway with fuzzy theorem. And we use a weighted Round Robin scheduling to achieve the different type video user with a ratio weighted delay-based drop quality.
Through the weighted Round Robin scheduling, the video service could achieve the maximum efficiency while under the acceptable delay bounds. And each user in the corresponding type is also fairly sharing the resources. The scheduling can help our CAC guarantee the maximum throughput and avoid much impact on the QoS of the existed users if the new call were accepted. In the CAC, we provide a approximation for estimate the new call bandwidth under the delay-based drop requirement. We design a fuzzy algorithm to apply in the WLAN protocol with SOHO/Home networks which is more popular in the future.
Bibliography
[1] IEEE Standard for Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Higher-Speed Physical Layer Extention in the 2.4 GHz Band, IEEE Std 802.11 1999, Sep. 1999.
[2] H. S. Chhaya and S. Gupta, “Performance modeling of asynchronous data transfer methods of IEEE 802.11 MAC protocol,” Wireless networks, vol. 3, pp. 217-234, Aug.
1997.
[3] G. Bianchi, “Performance analysis of the IEEE 802.11 distributed coordination function,”
IEEE J. Select Areas Commun., vol. 18, no. 3, pp. 535-546, March 2000.
[4] A. Kamerman and G. Aben, “Throughput performance of wireless LANs operating at 2.4 and 5 GHz, ” Proc. PIMRC’2000, pp. 190-194, Sep. 2000.
[5] D. J. Deng and R.S. Chang, “A priority scheme for IEEE 802.11 DCF access method ,
“ IEICE Trans. Commun., vol. E82-B, no. 1,pp. 96-102, Jan. 1999.
[6] B.P. Crow, I. Widjaja, J. G.. Kim, and P. T. Sakai, “ IEEE Commun. Mag., vol. 35, no. 9, pp. 116-126, Sep. 1997
[7] T. Suzuki and S. Tasaka, “Performance evaluation of video transmission with the PCF of the IEEE 802.11 standard MAC protocol,” IEICE Trans. Commun., vol. E83-B, no. 9, pp.
2068-2076, Sep. 200
[8] S. K. Sharma, K. Kim, C. Oh, and A. Ahmad, “Performance evaluation of IEEE 802.11 MAC protocol for multimedia services,” Proc. APCC/ICC’s98, pp. 181-185, 1998
[9] T. Suzuki and S. Tasaka, “Performance evaluation of priority-based multimedia transmission with the PCF in an IEEE 802.11 standard wireless LAN,＂Personal, Indoor and Mobile Radio Communications, vol. 2, pp.G-70 -G-77, Oct. 2001.
[10] IEEE Standard for Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Medium Access Control (MAC) Enhancements for Quality of Service (QoS), IEEE Std 802.11e/D6.0, November 2003.
[11] P. T. Brady, “A statistical analysis of on-off patterns in 16 conversations,” Bell Syst.Tech.J., vol. 47, pp. 73-91, Jan. 1968.
[12] D. L. Gall, “MPEG: A video compression standard for multimedia applications,”
Commun. of the ACM, vol. 34, no. 4, pp. 46-58, Apr. 1991.
[13] N. L. S. Fonseca and J. A. Silvester, “Modeling the output process of an ATM multiplexer with Markov modulated arrivals,” IEEE ICC ’94 , pp. 721-725, 1994.
[14] J. J. Bae, and T. Suda, “Survey of traffic control schemes and protocols in ATM networks,” Proc. of the IEEE, pp. 170-189, Feb. 1991.
[15] J. W. Roberts, “Variable-bit-rate traffic control in B-ISDN,” IEEE Commun. May., pp.
50-56, Sep. 1991.
[16] D. Qiao, S. Choi and K.G.. Shin, “Goodput analysis and link adaptation for IEEE 802.11a wireless LANs,” IEEE transactions on mobile computing, vol. 1, no. 4, pp.
278-292, Oct. 2002.
[17] A. Ganz and K. Wongthavarawat, “IEEE 802.11 wireless LAN association procedure for multimedia applications,” IEEE/MILCOM,vol 2, pp. 1287-1291, Nov. 1999)
[18] W. Willinger, M. Taqqu, R. Sherman, and D. Wilson, “Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level,” Proc.
ACM SIGCOMM 1995, pp. 100-113, Aug. 1995
[19] G. Kramer, B. Mukherjee, and G. Pesavento, “IPACT: A Dynamic Protocol for an Ethernet PON (EPON),” IEEE Commun. Mag., vol. 40, no. 2, pp. 74-80, Feb.2002.
[20] W. Leland, M. Taqqu, W. Willinger, and D. Wilson, “On the Self-Similar Nature of Ethernet Traffic (Extended Version),” IEEE/ACM Transactions on Networking, vol. 2, no. 1, pp. 1-15, Feb. 1994
[21] H.-J. Zimmermann, “Fuzzy set theory and its applications,” 2nd revised edition, Kluwer Academic Publishers, pp. 11-17, 1991.
[22] R. G.. Cheng, C. J. Chang, and L. F. Lin, ”A QoS-provisioning neural fuzzy connection admission controller for multimedia high-speed networks,” IEEE/ACM Trans.
Networking, vol. 7, no. 1, pp. 111-121, Feb. 1999.
Vita
姓名:吳俊憲 學歷:
2002~2004 國立交通大學電信工程研究所 1997~2002 國立交通大學土木工程系 1994~1997 台北市立建國高級中學
E-mail: [email protected]