# A New Adaptive FEC Loss Control Algorithm for Voice Over IP Applications

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4 The sender pseudocode for the USF algorithm is shown in Figure 3. A received RTCP packet contains the number of packets lost before reconstruction, the number of packets lost after reconstruction, and the number of packets lost in loss bursts. The value of combination (initialized to at the start of a voice session) is the index in Table. The sender calculates the percentage of packets lost before reconstruction and the percentage of packets lost after reconstruction at the receiver (lines 1 and ). As before, the combination number is not allowed to exceed the maximum value in Table or be less than zero - this check is not shown in the pseudocode. For each RTCP packet received do 1. Calculate packet loss after reconstruction, P a P a = Number of packets lost after reconstruction / Number of packets expected. Calculate packet loss before reconstruction, P b P b = Number of packets lost before reconstruction / Number of packets expected 3. If (P a > HIGH) then Subtract packets lost in loss bursts and recalculate P a. If (P a > HIGH) then Increment combination 5. If (P a < LOW) then Loss difference = P b (previous) - P b 6. If (Loss difference > MINIMUM_THRESHOLD) then Decrement combination 5. Set P b (previous) = P b Figure 3 - Sender pseudocode for the USF algorithm The values of HIGH and LOW correspond to target high and low packet loss rates for reconstructed packets (lines 3 and ). If the percentage of packets lost after reconstruction is greater than the HIGH mark then the number of packets not lost in bursts is calculated by subtracting the number of packets lost in loss bursts from the number of packets lost after reconstruction. The new percentage value is then checked with the value of HIGH. If this new percentage value is greater than HIGH then the combination number is increased. If the percentage of packets lost after reconstruction is lower than the LOW mark, then the percentage of packets lost in the previous RTCP interval is subtracted from the percentage of packets lost in this interval. If this difference is greater than the MINIMUM_THRESHOLD value, then the combination number is decreased. By comparing the values of the percentage of packet loss before reconstruction of the current period with that of the previous period, the USF algorithm considers the past network loss history before decreasing the amount of redundancy. This use of historical loss data is intended to prevent cyclical behavior. 5. Evaluation of the USF Algorithm The Bolot and USF algorithms were evaluated using a simulation model. 5.1 Inputs used for the simulation experiments The inputs to the simulation experiments were actual Internet voice packet traces collected by Yajnik et al. at the University of Massachusetts, Amherst [6] and synthetic traces. The Internet traces used in the experiments were collected by sending packet probes at regular intervals of ms, ms, 8ms and 16ms along unicast and multicast connections. This paper considers the traces with periodic intervals of ms and ms because these are the typical sampling times of VOIP applications. The receivers were at Los Angeles and Seattle for the ms traces and at Atlanta for the ms trace. Each packet has a unique sequence number that the receiver uses to keep track of packet loss [6]. Five Internet traces were used, see Table 3, with packet loss rates ranging from 1.38% to 3.76%. To generate the synthetic traces, the approach used in [3] was employed. A finite-buffer single-server queue models the bottleneck queue in the network path of a voice session. Arrivals at this queue consist of packets generated by interactive processes such as telnet and packets generated by bulk transfer applications such as FTP. Figure shows the queueing model. The simulation was implemented using the CSIM18 simulation engine [16]. Voice packets arrive at regular intervals of ms and the other packets have their arrival times exponentially distributed. The ratio of the number of interactive packets to the number of bulk transfer packets is taken as :6. The interactive packets are 3 bytes in length, the bulk transfer packets are 51 bytes, and the audio packets are 3 bytes. The bottleneck bandwidth is fixed at 51 Kbps. The rate of arrival of the interactive and bulk transfer packets at the server was increased to simulate loss rates in a range of 1.7% to 35% for the voice packets. Interactive packets Bulk data transfer packets Voice packets Finite buffer Packet loss Bottleneck Figure - Queueing model to generate synthetic traces

5 5. Simulation results for the Internet traces For the simulation experiments, the LOW and HIGH values were set to 3% for both the Bolot and USF algorithms. For the USF algorithm, the MINIMUM_THRESHOLD value was also set to 3%. The value 3% represents a reasonable loss value (i.e., loss rates of greater than 3% typically affect voice quality). The comparison results for the Bolot and USF algorithms with the five Internet traces as input are shown in Table 3 (the first column in Table 3 and is the trace number). The results (in the Ratio column) show that the USF algorithm maintains a loss rate after reconstruction of one-half to one-third that maintained by the Bolot algorithm. Table shows the absolute number of these 5-second periods for which the algorithms maintained a loss percentage greater than the HIGH mark. It can been seen (column 5 of Table ) that the USF algorithm maintains the desired loss rate over a greater number of periods (i.e., is more than the desired loss rate for fewer periods) than does the Bolot algorithm. This shows why the loss percentage is lower for the USF algorithm. Table 3 - Simulation results for Internet traces (loss) # Network Loss w/ Loss w/ Ratio Loss Bolot USF % 1.5 %.61 % Table - Simulation results for Internet traces (periods) # Total Periods Total Above Above w/ Bolot Above w/ USF Figures 5 and 6 show the number of packets lost after reconstruction for the Bolot and USF algorithms, respectively, for the first Internet trace. The difference in the number of packets lost by the two algorithms is shown in Figure 7. A positive value indicates that the USF algorithm performed better than the Bolot algorithm. It can be seen that the USF algorithm results in far fewer losses than the Bolot algorithm. The graphs for the remaining four traces are similar in appearance to that of the first trace and are not shown. Packets lost after reconstruction Figure 5 - Number of packets lost by Bolot algorithm Packets lost after reconstruction Figure 6 - Number of packets lost by USF algorithm Difference in packets lost Period number Period number Period number Figure 7 - Difference in the number of packets lost 5.3 Simulation results for synthetic traces Table 5 shows the result of the simulation experiments for the synthetic trace input. The target loss rate after reconstruction was set to 3%. Figure 8 plots the variation in the loss rates for the two algorithms along

6 with the network loss rates. The results show that the USF algorithm maintains one-third the loss rate maintained by Bolot algorithm when the network loss rate is below 7%. Network loss rate (%) Table 5 - Simulation results for the synthetic trace Network Loss w/ Loss w/ Ratio Loss Bolot USF 1.67 % 1.66 %.56 % Network loss rate Loss rate for the Bolot algorithm Loss rate for the USF algorithm Desired loss rate = 3% Trace number Figure 8 - Variation in loss rate for the synthetic traces The Bolot algorithm performs better than the USF algorithm for a network loss rate between 9% to 13%. The accuracy of the Bolot reward value for the synthetic traces was studied by plotting the actual percentage loss after reconstruction against the percentage loss calculated by the Bolot algorithm for the trace with a network loss rate of 13%. If the Bolot algorithm were accurate in calculating the packet loss after reconstruction using the reward value then most of the points in the graph would lie along the diagonal. It can be seen in Figure 9 that many points lie above the diagonal for low loss rates. This indicates that the Bolot algorithm can overestimate the loss rate after reconstruction. Loss calculated by Bolot algorithm (%) Figure 9 - Error in packet loss by Bolot algorithm The performance of the Bolot algorithm was simulated using the loss rate after reconstruction directly. Table 8 and Figure show the results. The USF algorithm still performs better than the Bolot algorithm. Network loss rate (%) Table 8 - Loss after direct reconstruction for Bolot Network Loss w/ Loss w/ Ratio Loss Bolot USF 1.67 % 1.6 %.56 % Actual loss after reconstruction (%) Network loss rate Loss rate for Bolot algorithm Loss rate for USF algorithm Ideal value Desired loss rate = 3% Trace number Figure - Loss after direct reconstruction for Bolot

7 6. Conclusions and Future Work This paper described a new redundancy control algorithm - the USF algorithm - for VOIP applications. A recently presented control algorithm presented in [] by Bolot et al. is codec specific and assumes that the network loss process is a Bernoulli process. A previous control algorithm also by Bolot et al. [5], called the Bolot algorithm, uses empirically determined reward values to select the level of redundancy to be used. The USF algorithm dynamically changes the amount of redundancy added to a packet stream at the sender as a function of the actual measured packet loss rate. The USF algorithm uses the number of packets lost after reconstruction as a measure of the effectiveness of its FEC scheme. In addition, the USF algorithm detects loss bursts and considers the network packet loss history before changing the amount of redundancy. The USF algorithm was evaluated using a simulation model with both actual packet voice traces from the Internet and synthetic traces with a loss rate ranging from 1.5% to 35%. For the Internet traces, the loss rate experienced by a voice application using the USF algorithm was one-half to onethird the loss rate experienced using the Bolot algorithm. For the synthetic traces, the USF algorithm maintains a loss rate one-half to one-third of that maintained by the Bolot algorithm for network loss rates of 7% to %. Future work should quantify the bandwidth savings possible from the USF algorithm. The amount of bandwidth savings is highly dependent on the codecs used in the implementation of an algorithm (USF and Bolot). More work also needs to be done on setting MINIMUM_THRESHOLD values for the USF algorithm. Finally, additional experiments should be conducted with a wider range of Internet voice packet trace files. Acknowledgements The authors would like to thank Maya Yajnik and Sue B. Moon of the University of Massachusetts, Amherst for making their Internet voice packet traces available. The authors would also like to thank Jean-Chrysotome Bolot for his comments and clarifications. References [1] A. Albanese, J. Blomer, J. Edmonds, M. Luby, and M. Sudan, Priority Encoding Transmission, IEEE Transactions on Information Theory, Vol., No. 6, pp , November [] E. Biersack, A Simulation Study of Forward Error Correction in ATM Networks, Computer Communications Review, Vol., No. 1, pp. 36-7, January 199. [3] J-C. Bolot, Analysis of Audio Packet Loss in the Internet, Proceedings of NOSSDAV, pp , April [] J-C. Bolot, S. Fosse-Parisis, and D. Towsley, Adaptive FEC-Based Error Control for Internet Telephony, Proceedings of IEEE INFOCOM, March [5] J-C. Bolot and A. Garcia, Control Mechanisms for Packet Audio in the Internet, Proceedings of IEEE INFOCOM, pp. 3-39, March [6] M. Borella, D. Swider, S. Uludag, and G. Brewster, Internet Packet Loss: Measurement and Implications for End-to-End QoS, Proceedings of the ICPP Workshop on Architectural and OS Support for Multimedia Applications Flexible Communications Systems, pp. 3-1, August [7] B. Dempsey, J. Liebeherr, and A. Weaver, On Retransmission-Based Error Control for Continuous Media Traffic in Packet-Switching Networks, Technical Report CS-9-9, Computer Science Department, University of Virginia, February 199. [8] Free Phone, February 19, URL: [9] V. Hardman, M. Sasse, M. Handley and A. Watson, Reliable Audio for Use Over the Internet, Proceedings of INET, [] O. Hodson, S. Varakliotis, and V. Hardman, A Software Platform for Multiway Audio Distribution Over the Internet, IEE Colloquium on Audio and Music Technology: The Challenge of Creative DSP, pp , November [11] N. Jayant and S. W. Christensen, Effects of Packet Losses in Waveform Coded Speech and Improvements due to an Odd-Even Sample-Interpolation Procedure, IEEE Transactions on Communications, Vol. COM-9, No., pp. 1-9, February [1] I. Kouvelas, O. Hodson, V. Hardman and J. Crowcroft, Redundancy Control in Real-Time Internet Audio Conferencing, Proceedings of the 1997 International Workshop on Audio-Visual Services Over Packet Networks, September [13] C. Perkins, O. Hodson, and V. Hardman, A Survey of Packet Loss Recovery Techniques for Streaming Audio, IEEE Network, Vol. 1, No. 5, pp. - 8, September- October [1] H. Schulzrinne, Voice Communication Across the Internet: A Network Voice Terminal, Technical report, Department of Computer Science, University of Massachusetts, July 199. [15] H. Schulzrinne, S. Casner, R. Fredrick and V. Jacobson, RTP: A Transport Protocol for Real-Time Applications, Internet Engineering Task Force, RFC 1889, January [16] H. Schwetman, CSIM18 - The Simulation Engine, Proceedings of the 1996 Winter Simulation Conference, pp , [17] A. Watson and M. Sasse, Measuring Perceived Quality of Speech and Video in Multimedia Conferencing Applications, Proceedings of ACM Multimedia, pp. 55-6, September 1998.

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