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Dear chair:
 
  We  have written this draft in the attachment. We would like to standardize it and would be thankful for comments. We hope that you can send the email to the DCCP list. Thank you very much!
 
 
 Sincerely Yours,
 Yu-ning Dong, Hai-tao Zhao
 Best regards!
                                                                     
                                                                     
                                                                     
                                             

Datagram Congestion Control		                Yu-ning Dong
Internet Draft	                                        Hai-tao Zhao
Intended status: Experimental    Nanjing Univ. of Posts and Telecom.
Expires: April 2011                                 October 26, 2010


A Wireless Channel Model Based Rate Control (WMRC) Scheme in RTP/UDP
for Real Time Multimedia Transmissions over Wired-Wireless Networks
                        (WMRC-RTP/UDP)
                draft-dong-wmrc-rtpcontrol-00.txt


Status of this Memo

   This document is an Internet-Draft and is subject to all provisions
   of section 3 of RFC 3667. By submitting this Internet-Draft, each
   author represents that any applicable patent or other IPR claims of
   which he or she is aware have been or will be disclosed, and any of
   which he or she become aware will be disclosed, in accordance with
   RFC 3668.

   Internet-Drafts are working documents of the Internet Engineering
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   This Internet-Draft will expire on April 26, 2011.

Copyright Notice

   Copyright (c) 2010 IETF Trust and the persons identified as the
   document authors. All rights reserved.

Abstract

   This document introduces a Wireless Channel Model Based rate control
   scheme for improving the behavior of real time multimedia streams




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    with TFRC [1] in wireless-wired heterogeneous networks. Based on
    wireless channel characteristics, the method can first identify the
    level of packet losses of two different types by sending large and
    small packets alternately, then adopt different adaptive rate
    control strategies to increase the network throughput and decrease
    congestion packet loss rate, to improve transmission quality of
    real-time multimedia stream. The proposed method is compared with
    previously reported algorithms [2-3] by simulation. It is shown from
    the simulation results in different network topology environments,
    the performance the proposed algorithm is better than existing
    algorithms in the aspects of network bandwidth utilization and
    congestion packet loss control. Parts of this method published in
    the IEEE Wireless Communications and Networking Conference (WCNC2007)
    and in a pending China patent (access number: CN101686100).

Table of Contents

   1.  Introduction. . . . . . . . . . . . . . . . . . . . . .  2
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . .  3
   3.  Packet Loss Discrimination. . . . . . . . . . . . . . .  3
   4.  Adaptation to Network State Changes . . . . . . . . . .  7
   5.  WMRC Behavior Description . . . . . . . . . . . . . . .  8
       5.1. Adaptive Rate Control Mechanism. . . . . . . . . .  8
       5.2. WMRC Specific Implementation Steps . . . . . . . .  9
   6.  Security Considerations . . . . . . . . . . . . . . . . 10
   7.  IANA Considerations . . . . . . . . . . . . . . . . . . 10
   8.  Conclusions . . . . . . . . . . . . . . . . . . . . . . 10
   9.  References. . . . . . . . . . . . . . . . . . . . . . . 11
       9.1. Informative References . . . . . . . . . . . . . . 11
   10. Acknowledgments . . . . . . . . . . . . . . . . . . . . 11

1.  Introduction

   This document describes a wireless channel model based packet loss
   discrimination method that can differentiate wireless random bit
   error packet loss from congestion packet loss over wireless-wired
   networks. This work focuses on how to obtain the dynamic change 
   characteristics of wireless communication network from the
   transport/application layer, and to achieve a better end-to-end 
   quality of service by making adaptive adjustment according to these
   changes. The proposed scheme shows to be more accurate than existing 
   methods in estimating current network status by means of a wireless
   channel model and statistical analysis of large and small packets
   loss rates, and its performance basically not affected by the
   variation of network topology and the competition flows. The real-




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   time multimedia transmission protocol can carry out performance
   optimization based on the packet loss discrimination results. For
   example, if only the wireless losses are reported, the source and
   channel coding ratio can be adjusted to increase the data protection 
   instead of reducing sending rate.

2.  Terminology

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this 
   document are to be interpreted as described in RFC-2119 [RFC2119].

3.  Packet Loss Discrimination

   Previous research indicates that the packet loss probability caused
   by random bit errors is related to the packet size in wireless
   environment, namely, the larger the packet size, the higher the
   packet loss probability. The congestion packet losses (drop-tail
   router), however, are generally independent of the packet size.
   Based on this observation, one can send small probing packets
   regularly to the channel to distinguish from the large-size video
   packets, and estimate current main cause of packet losses from their
   feedback information. However, channel bandwidth utilization will be
   reduced by these probing packets. Therefore, we use small-size video
   packets instead of probing packet to improve channel bandwidth
   utilization. A method for identifying packet loss reason from the
   packet loss rates of large and small packets is developed below.
    
   In order to identify between congestion packet losses and wireless
   fading losses, the sender node sends large and small packets 
   alternately and the statistics of the lost large and small packets 
   over a period is calculated at the receiver end. For ease of analysis,
   let us define the following variables:

      Nps = the number of lost small packets;

      Npsc = the number of lost small packets due to congestions;

      Npsb = the number of lost small packets due to bit errors;

      Npl = the number of lost large packets;

      Nplc = the number of lost large packets due to congestions;

      Nplb = the number of lost large packets due to bit errors.





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   According to traditional communication theory, the wireless packet
   loss rate varies exponentially with the channel bit error rate r. In
   some cases such as uniform distribution with a very small r, the
   variations of packet loss rate with r can be approximated by a
   linear function. For the wired channel, as mentioned above, the
   numbers of large and small congestion packet losses in the given 
   period would approximately be equal, namely Nplc=Npsc. Thus, we have 
   the following equations:

      Npl = Nplc + Nplb (1)

      Nps = Npsc + Npsb (2)

   Let B denote the ratio of Nplb to Npsb in certain wireless channel
   condition. Obviously, B is a function of the channel bit error rate 
   r and can be expressed as:

      B(r) = Nplb / Npsb (3)

   Thus, equation (1) can be rewritten as:   

      Npl = Npsc + B(r) * Npsb (4)

   At the receiver end, one can obtain the statistical values of Npl and 
   Nps over a time interval. If B is known, one can get the values of 
   Nplc (=Npsc), Nplb and Npsb by solving above equations, namely, the 
   congestion loss rate and random erroneous loss rate of large and 
   small packets respectively. One can then know current congestion 
   level of the wired networks from Nplc and Npsc, and fading condition 
   of the wireless link from Nplb and Npsb.
   
   The problem now is how to know the value of B, and there seems very
   few works have been done on this issue. In [4], B was assumed to be a
   constant, dependent on the sizes of large and small packets. This
   however is not always true according to our experimental results.
   Therefore, by taking this assumption in solving equations (2) through
   (4) for other variables, the applicable scope of the obtained values
   will probably be rather limited.
   
   To analyze the relations between packet loss rates and the packet
   sizes, a group of experimental tests in wireless channels have been
   carried out by using a modified Jakes Rayleigh fading model [5] in
   different channel BERs (Bit Error Rates) and packet sizes. Linear,
   quadratic and exponential curves are used to fit the obtained
   simulation data where the exponential fitting has the largest fitting
   errors.





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   Let G denote packet length, and assume the random bit error of a
   wireless channel is subject to uniform distribution and any two bit
   error events are uncorrelated. The packet loss error rate P of
   wireless link can thus be computed as

      P=1-(1-r)^G (5)
 
   If r is very small, by Taylor expansion in r = 0 and omitting higher
   order terms, the linear (first-order) and second-order approximation
   of equation (5) can be obtained as follows,

   Linear approximation (first order): P=r*G (6)

   Second-order approximation: P=r*G*(1-r*G/2) (7)

   If the linear approximation is used, we have,

      Pl/Ps = Gl/Gs = b (8)

   Where Pl and Ps are the loss rate of large and small packets
   respectively; Gl and Gs are the lengths of large and small packet
   respectively; b denotes the ratio of the large packet length to small
   packet length. B in this condition is a constant (=b), which is
   frequently used in previous literatures. However, when r is not small
   enough, the above equation is not applicable. At this time, one can
   consider second-order approximation and the ratio can be obtained
   from equation (7) as,

                 2-r*b*Gs
      Pl/Ps = b*----------- = b*A(r) (9)
                  2-r*Gs
   
   Where A(r) = (2-r*b*Gs)/ (2-r*Gs) (10)

   When b = 2, the above equation becomes,

      A(r) = (1-r*Gs)/ (1-r*Gs/2) (11)
 
   From above analysis, we can see that, when r is not small enough,
   Pl/Ps is not a constant but determined by A. In most practical
   settings, the reasonable value scope of A in equation (11) is 0.6~1
   on condition that r<4/7*Gs (In fact, this is not a necessary
   condition). For example, when Gs=4000bits (500Bytes), then r<1.4*10^-
   4, and when Gs=800bits (100Bytes), r<7.1*10^-4. That is to say, the
   bit error rate is kept in a small or medium value range. Otherwise,




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   the second-order approximation (equation (7)) may not be applicable.
   A(r) monotonically decreases for a given value G with the increase of
   r.

   On the other hand, let us define the following variable,
   
      &N = Npl ? Nps = Nplc + Nplb ? Npsc ? Npsb = Nplb ? Npsb = &Nb
      (Since Nplc =Npsc) (12)

   From equation (12), we can know that the difference between the
   number of lost large and small packets is equal to the difference
   between the number of lost large and small packets due to bit errors.
   The wireless packet loss rate P increases linearly with packet size
   under certain r ranges, namely,

      &P=k*&G (13)
 
   Where &P=Pl-Ps, &G=Gl-Gs and k (k>0) is an r-related constant. Since
   &P can be calculated from equation (12), and &G is known in advance,
   constant k can be obtained, that reflects the degree of link bit
   errors.

   The slope of packet loss rate curve decreases with packet length
   increase when BER is relatively high; while the curve slope almost
   keeps stable and uncorrelated to packet length when BER is small,
   namely, the packet loss rate varies linearly with packet length under
   small BER conditions. Therefore, one can estimate the current level
   of r from k within the scope of r<1.8*10^-4.

   As for congestion packet losses in wired networks, the adaptive rate
   control mechanism TFRC[1], decreases the sending rate when high
   packet loss rate is reported, and allows the loss rate to decrease
   quickly (assuming the video stream shares the network bandwidth with
   other TCP-friendly traffic) [6]. According to our NS2 simulation
   results, the packet loss rate can normally drop by more than 50%
   within 4 RTT (Round Trip Time) time.

   Based on above analyses, we propose the following computation
   strategy:

   1) When the packet loss rate rises to an unacceptable level, the rate
   control mechanism will decrease the sending rate. Thus, (1) If this
   high loss rate is due to congestions of the wired link, then as
   discussed above, the loss rate will drop considerably within several
   RTTs; (2) If however, the loss rate doesn’t show any obvious drop
   within the time interval, one may regard present packet losses most




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   probably due to the bit errors of the wireless link rather than
   network congestions.

   2) If present packet losses are indeed mainly due to bit errors of
   the wireless link, we may assume the number of congestion packet
   losses Npsc in (2) and (4) much less than the number of erroneous
   packet losses Npsb, and Nplc << Nplb. Equations (2) and (4) can then
   be simplified as:

      Nps = Npsb (14)

      Npl = B(r)*Npsb (15)

   From above equations, one can estimate the value of B, and at the
   same time identify the main cause of current packet losses. Note that
   in our method, there is no assumption of the linear correlation of
   the erroneous packet loss rate with the packet size.

   3) A linear prediction with error correction method is adopted to
   estimate the value of B. If present packet losses are mainly due to
   bit errors of the wireless link, then

      Bt = d*Bt - 1 + (1-d)*&Bt (B0 is the initial value) (16a)

      Otherwise, Bt=B0 (16b)
 
   Where B0=Gl/Gs; &Bt=Npl/Nps is the prediction error corrective value;
   d is a weighting coefficient (0<d<1); t=1,2,…, denotes sampling
   time with sampling interval &t=q*RTT (q>0, a constant).
   
   As mentioned above, B is no longer a constant when wireless random
   bit errors are high. Therefore, we adopt the linear prediction with
   error correction (corrective value &Bt) method to gradually track the
   value of B as shown in equation (16a). The weighting coefficient d
   determines tracking speed of Bt to the real value of B that is not a
   constant, and the selection of d should compromise between tracking
   speed and stability of B. Equation (16b) represents the case of low
   BER of wireless link, where packet losses are mainly due to network
   congestion and B can be approximated by a constant (see equation (8)).

4. Adaptation to Network State Changes

   For timely response to the change of network status, a finite length
   history record based large and small packet loss statistics is used.
   In a sliding window, Nps and Npl record the lost number of small and
   large packets respectively. When a new packet loss occurs, the oldest
   recorded one will be removed from the record queue, and the




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   statistical value will be updated correspondingly. The main concern
   here is the selection of the queue length: on one hand, if the queue
   is shorter, the response to the change of network status will be
   quick, but may cause stability problem; on the other hand, if the
   queue is too long, the sending rate will be relatively stable, but
   the response to network state changes may be slow. Therefore, the
   length of lost packets record queue represents a compromise between
   response time and control stability.

   In order to track the change of the network states effectively, we
   introduce another statistic to help determine the current network
   states. Let,
 
      Dec = 2*(B*Ps-Pl) / ((B-1)*(Ps+Pl)) (17)

      And, Pc = (Npsc+Nplc) / (Nps+Npl) (18)

   From equations (1)-(4), one can see that the statistic Dec is equal
   to Pc in a statistical sense, and reflects the ratio of the number of
   congestion packet losses to the number of total lost packets.
   Therefore, the value of Dec also reflects the congestion/wireless
   packet loss status of current networks. The larger the value is, the
   more serious the congestion packet losses. The values of Pl and Ps in
   equation (17) are calculated by the reciprocal of the average length
   of intervals of packet loss events [1].

   The advantage of calculating Dec by equation (17) is: if no packet
   loss happens for a long time, although no new packet loss event
   occurs, the interval between packet loss events gets longer, and the
   congestion reduction can be reflected timely by the weighting
   coefficient of sliding window. This means the weight of loss events
   that occur more recently is larger, and that of older loss events is
   smaller. In this way, we can track current network status more
   quickly, and at the same time achieve good control stability.

5. WMRC Behavior Description

5.1.  Adaptive Rate Control Mechanism

   To satisfy the TCP friendliness requirement, an adaptive rate control
   based on TCP throughput model is used in this paper. The used TCP
   throughput mathematical model is as follows [1]:

                                       TU
      rate= ------------------------------------------------------- (19)
            RTT*sqrt(2*p/3) + (4*tout*(3*sqrt(3*p/8)*p*(1+32*p^2)))





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   Where, TU denotes data packet size, RTT denotes round trip time, tout
   denotes retransmission timeout time (tout = 4 RTTs), P denotes packet
   loss rate. Equation (19) works well in wired IP environment, but in
   wireless environment, the performance of conventional TCP/TFRC is
   often unsatisfactory. Therefore, we modify this model a bit by
   removing the number of lost packets due to wireless bit errors in the
   calculation of P. Thus the capability to differentiate the packet
   loss types will be essential.

   In the WMRC algorithm, when the receiver detects a packet loss event,
   it calculates the Dec first, then judges whether it is a congestion
   packet loss by comparing the value of Dec with a given threshold Dth
   (0<Dth<1). If it is judged as a congestion packet loss (Dec > Dth),
   this packet loss event will be used in the calculation of packet loss
   rate P in Equation (19); otherwise, it won't be. Thus, the packet
   loss rate P obtained from the RTCP feedback packets at the sender
   reflects only the congestion packet loss rate, not including the
   wireless packet losses. And the calculated sending rate will be fit
   the current network situation well. Then, the situation of excessive
   restriction of the sending rate will not happen. The smaller the
   value of Dth is, the greater the possibility of judging the current
   packet loss as the congestion loss; conversely, the greater the
   possibility of judging it as the wireless random packet loss. We
   generally set Dth=0.8 after running a number of experimental tests.

5.2. WMRC Specific Implementation Steps

   The proposed scheme is based on RTP/UDP transport layer protocol [7],
   and works in following steps:

   1) Initialization: after setting the initial sending rate, the
   parameters of a, b, d, q, Gl, Gs, Dth, and the length of record queue
   of packet losses, the algorithm enters a slow start stage.

   2) When the media streaming gets into a stable state when packet loss
   occurs, the receiver end computes the statistical values of Npl, Nps,
   Pl, Ps, RTT, and P (recording the congestion packet loss rate only).

   3) The receiver end calculates the value of Dec by equation (17) for
   every packet loss event, and estimates the reason of the current
   packet loss. If Dec > Dth, the packet loss is judged as the
   congestion loss, otherwise, the wireless packet loss. If it is a
   congestion packet loss, it will be used to update the packet loss
   rate P; otherwise it will not be. At every sampling time point t, Bt
   is updated by equation (16) according to the nature of the current
   packet loss. At every certain time interval, the receiver informs the
   sender the RTT and packet loss rate P by RTCP feedback packets.





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   4) If there are packet losses occurred during the feedback period,
   when the sender receives the RTCP feedback packets, rate control will
   be carried out according to the equation (19). Otherwise, a MIMD(a, b)
   congestion control scheme [8] will be adopted.

6. Security Considerations
 
   WMRC is not a transport protocol in its own right, but a congestion
   control mechanism that is intended to be used in conjunction with a
   transport protocol. Therefore security primarily needs to be
   considered in the context of a specific transport protocol and its
   authentication mechanisms. Congestion control mechanisms can
   potentially be exploited to create denial of service. This may occur
   through spoofed feedback. Thus any transport protocol that uses WMRC
   should take care to ensure that feedback is only accepted from the
   receiver of the data. The precise mechanism to achieve this will
   however depend on the transport protocol itself.

   In addition, congestion control mechanisms may potentially be
   manipulated by a greedy receiver that wishes to receive more than its
   fair share of network bandwidth. A receiver might do this by claiming
   to have received packets that in fact were lost due to congestion.
   Possible defenses against such a receiver would normally include some
   form of nonce that the receiver must feed back to the sender to prove
   receipt. However, the details of such a nonce would depend on the
   transport protocol, and in particular on whether the transport
   protocol is reliable or unreliable.

   We expect that protocols incorporating large/small packet with WMRC
   will also want to incorporate feedback from the receiver to the
   sender using packet loss discrimination. The packet loss
   discrimination is a modification to TFRC that distinguishes the loss
   packets from congestion loss or wireless random error.

7. IANA Considerations

   There are no IANA actions required for this document.

8. Conclusions

   This document presents a wireless channel model based rate control
   scheme WMRC for wireless multimedia transmission control over hybrid
   networks. This scheme can detect the network status and differentiate
   packet loss types (wireless or congestion losses) by means of a
   wireless channel model and a special packet sending scheme with
   different packet sizes. It can adapt to the dynamic change of the
   networks and control the sending rate effectively. Theoretical




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   analysis and detailed implementation of the proposed scheme are given.
   At the same time, it should be noted that due to the use of large and
   small packets alternately in the proposed algorithm, the application
   layer needs to pack data into two different-size packets for
   transmission, which may increase the overhead of packing process.

9. References
 
9.1. Informative References
 
   [1] Floyd, S., Handley, M., Padhye, J., and J. Widmer, "TCP
   Friendly Rate Control (TFRC): Protocol Specification", RFC 5348,
   September 2008.

   [2] Song Cen, et al, “End-to-End Differentiation of Congestion and
   Wireless Losses,” IEEE/ACM Transactions on Networking, vol. 11,
   no. 5, pp. 703-717, October 2003.

   [3] Min Kyu Park, Kue-Hwan Sihn, Jun Ho Jeong, “A Statistical
   Method of Packet Loss Type Discrimination in Wired-Wireless
   Networks,” Proc. IEEE CCNC, 2006, pp. 458-462.

   [4] C. L. Lee, et al, “On the Use of Loss History for Performance
   Improvement of TCP over Wireless Networks”, IEICE Trans.
   Commun. , vol. E85-B, no. 11, pp. 2457-2467, 2002.

   [5] H.-J. Lee, H.-J. Byun, and J.-T. Lim, “TCP-friendly congestion
   control for streaming real-time applications over wireless
   networks”, IET Commun., vol. 2, no. 1, pp. 159?163, 2008.

   [6] S. Floyd and J. Padhye, “Equation-Based congestion control for
   unicast applications”, Proc. ACM SIGCOMM’00, 2000, pp. 43-56.

   [7] Schulzrinne, H., Casner, S., Frederick, R. and V. Jacobson,
   "RTP: A Transport Protocol for Real-Time Applications", RFC
   1889, January 1996.

   [8] Yu-ning Dong and Meng-yue Chen, “Real time video transmission
   control in wireless-wired IP networks”, Proc. IEEE Wireless
   Communications and Networking Conference (WCNC2007), Hong Kong,
   Mar. 2007, pp. 3687-3691.

10. Acknowledgments

   The authors would like to acknowledge feedback and discussions on
   equation-based congestion control with a wide range of people,
   including members of the Wireless Communication Research Group and




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   the End-to-End Research Group. Thanks are given to the National
   Natural Science Foundation of China (No.60972038), the Jiangsu
   Province Universities Natural Science Research Key Grant Project
   (07KJA51006), and Jiangsu Province Graduate Innovative Research Plan
   (CX09B_149Z) for their financial support.

Authors’ Addresses

   Yu-ning Dong
   Nanjing University of Posts and Telecommunications PO Box 166
   66 New Mo-fan-ma-lu Road, Nanjing, Jiangsu, 210003
   China

   Email: dongyn@xxxxxxxxxxxx


   Hai-tao Zhao
   Nanjing University of Posts and Telecommunications PO Box 54
   66 New Mo-fan-ma-lu Road, Nanjing, Jiangsu, 210003
   China

   Email: zhaohtmail@xxxxxxxxx



























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