Network Working Group X. Zhu Internet-Draft R. Pan Intended status: Experimental M. Ramalho Expires: September 19, 2016 S. Mena P. Jones J. Fu Cisco Systems S. D'Aronco EPFL C. Ganzhorn March 18, 2016 NADA: A Unified Congestion Control Scheme for Real-Time Media draft-ietf-rmcat-nada-02 Abstract This document describes NADA (network-assisted dynamic adaptation), a novel congestion control scheme for interactive real-time media applications, such as video conferencing. In the proposed scheme, the sender regulates its sending rate based on either implicit or explicit congestion signaling, in a unified approach. The scheme can benefit from explicit congestion notification (ECN) markings from network nodes. It also maintains consistent sender behavior in the absence of such markings, by reacting to queuing delays and packet losses instead. Status of This Memo This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF). Note that other groups may also distribute working documents as Internet-Drafts. The list of current Internet- Drafts is at http://datatracker.ietf.org/drafts/current/. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." This Internet-Draft will expire on September 19, 2016. Zhu, et al. Expires September 19, 2016 [Page 1] Internet-Draft NADA March 2016 Copyright Notice Copyright (c) 2016 IETF Trust and the persons identified as the document authors. All rights reserved. This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents (http://trustee.ietf.org/license-info) in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Code Components extracted from this document must include Simplified BSD License text as described in Section 4.e of the Trust Legal Provisions and are provided without warranty as described in the Simplified BSD License. Table of Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3 2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3 3. System Overview . . . . . . . . . . . . . . . . . . . . . . . 3 4. Core Congestion Control Algorithm . . . . . . . . . . . . . . 5 4.1. Mathematical Notations . . . . . . . . . . . . . . . . . 5 4.2. Receiver-Side Algorithm . . . . . . . . . . . . . . . . . 8 4.3. Sender-Side Algorithm . . . . . . . . . . . . . . . . . . 10 5. Practical Implementation of NADA . . . . . . . . . . . . . . 12 5.1. Receiver-Side Operation . . . . . . . . . . . . . . . . . 12 5.1.1. Estimation of one-way delay and queuing delay . . . . 12 5.1.2. Estimation of packet loss/marking ratio . . . . . . . 12 5.1.3. Estimation of receiving rate . . . . . . . . . . . . 13 5.2. Sender-Side Operation . . . . . . . . . . . . . . . . . . 13 5.2.1. Rate shaping buffer . . . . . . . . . . . . . . . . . 14 5.2.2. Adjusting video target rate and sending rate . . . . 15 5.3. Feedback Message Requirements . . . . . . . . . . . . . . 15 6. Discussions and Further Investigations . . . . . . . . . . . 16 6.1. Choice of delay metrics . . . . . . . . . . . . . . . . . 16 6.2. Method for delay, loss, and marking ratio estimation . . 16 6.3. Impact of parameter values . . . . . . . . . . . . . . . 17 6.4. Sender-based vs. receiver-based calculation . . . . . . . 18 6.5. Incremental deployment . . . . . . . . . . . . . . . . . 18 7. Implementation Status . . . . . . . . . . . . . . . . . . . . 18 8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 19 9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 19 10. References . . . . . . . . . . . . . . . . . . . . . . . . . 19 10.1. Normative References . . . . . . . . . . . . . . . . . . 19 10.2. Informative References . . . . . . . . . . . . . . . . . 20 Appendix A. Network Node Operations . . . . . . . . . . . . . . 21 A.1. Default behavior of drop tail queues . . . . . . . . . . 22 A.2. RED-based ECN marking . . . . . . . . . . . . . . . . . . 22 Zhu, et al. Expires September 19, 2016 [Page 2] Internet-Draft NADA March 2016 A.3. Random Early Marking with Virtual Queues . . . . . . . . 22 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 23 1. Introduction Interactive real-time media applications introduce a unique set of challenges for congestion control. Unlike TCP, the mechanism used for real-time media needs to adapt quickly to instantaneous bandwidth changes, accommodate fluctuations in the output of video encoder rate control, and cause low queuing delay over the network. An ideal scheme should also make effective use of all types of congestion signals, including packet loss, queuing delay, and explicit congestion notification (ECN) [RFC3168] markings. The requirements for the congestion control algorithm are outlined in [I-D.ietf-rmcat-cc-requirements]. This document describes an experimental congestion control scheme called network-assisted dynamic adaptation (NADA). The NADA design benefits from explicit congestion control signals (e.g., ECN markings) from the network, yet also operates when only implicit congestion indicators (delay and/or loss) are available. Such a unified sender behavior distinguishes NADA from other congestion control schemes for real-time media. In addition, its core congestion control algorithm is designed to guarantee stability for path round-trip-times (RTTs) below a prescribed bound (e.g., 250ms with default parameter choices). It further supports weighted bandwidth sharing among competing video flows with different priorities. The signaling mechanism consists of standard RTP timestamp [RFC3550] and RTCP feedback reports with non-standard messages. 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 [RFC2119]. 3. System Overview Figure 1 shows the end-to-end system for real-time media transport that NADA operates in. Note that there also exist network nodes along the reverse (potentially uncongested) path that the RTCP feedback reports traverse. Those network nodes are not shown in the figure for sake of abrevity. Zhu, et al. Expires September 19, 2016 [Page 3] Internet-Draft NADA March 2016 +---------+ r_vin +--------+ +--------+ +----------+ | Media |<--------| RTP | |Network | | RTP | | Encoder |========>| Sender |=======>| Node |====>| Receiver | +---------+ r_vout +--------+ r_send +--------+ +----------+ /|\ | | | +---------------------------------+ RTCP Feedback Report Figure 1: System Overview o Media encoder with rate control capabilities. It encodes raw media (audio and video) frames into compressed bitstream which is later packetized into RTP packets. As discussed in [I-D.ietf-rmcat-video-traffic-model], the actual output rate from the encoder r_vout may fluctuate around the target r_vin. Furthermore, it is possible that the encoder can only react to bit rate changes at rather coarse time intervals, e.g., once every 0.5 seconds. o RTP sender: responsible for calculating the NADA reference rate based on network congestion indicators (delay, loss, or ECN marking reports from the receiver), for updating the video encoder with a new target rate r_vin, and for regulating the actual sending rate r_send accordingly. The RTP sender also generates a sending timestamp for each outgoing packet. o RTP receiver: responsible for measuring and estimating end-to-end delay (based on sender timestamp), packet loss (based on RTP sequence number), ECN marking ratios (based on [RFC6679]), and receiving rate (r_recv) of the flow. It calculates the aggregated congestion signal (x_curr) that accounts for queuing delay, ECN markings, and packet losses. The receiver also determines the mode for sender rate adaptation (rmode) based on whether the flow has encountered any standing non-zero congestion. The receiver sends periodic RTCP reports back to the sender, containing values of x_curr, rmode, and r_recv. o Network node with several modes of operation. The system can work with the default behavior of a simple drop tail queue. It can also benefit from advanced AQM features such as PIE, FQ-CoDel, RED-based ECN marking, and PCN marking using a token bucket algorithm. Note that network node operation is out of control for the design of NADA. Zhu, et al. Expires September 19, 2016 [Page 4] Internet-Draft NADA March 2016 4. Core Congestion Control Algorithm Like TCP-Friendly Rate Control (TFRC) [Floyd-CCR00] [RFC5348], NADA is a rate-based congestion control algorithm. In its simplest form, the sender reacts to the collection of network congestion indicators in the form of an aggregated congestion signal, and operates in one of two modes: o Accelerated ramp-up: when the bottleneck is deemed to be underutilized, the rate increases multiplicatively with respect to the rate of previously successful transmissions. The rate increase mutliplier (gamma) is calculated based on observed round- trip-time and target feedback interval, so as to limit self- inflicted queuing delay. o Gradual rate update: in the presence of non-zero aggregate congestion signal, the sending rate is adjusted in reaction to both its value (x_curr) and its change in value (x_diff). This section introduces the list of mathematical notations and describes the core congestion control algorithm at the sender and receiver, respectively. Additional details on recommended practical implementations are described in Section 5.1 and Section 5.2. 4.1. Mathematical Notations This section summarizes the list of variables and parameters used in the NADA algorithm. Zhu, et al. Expires September 19, 2016 [Page 5] Internet-Draft NADA March 2016 +--------------+-------------------------------------------------+ | Notation | Variable Name | +--------------+-------------------------------------------------+ | t_curr | Current timestamp | | t_last | Last time sending/receiving a feedback | | delta | Observed interval between current and previous | | | feedback reports: delta = t_curr-t_last | | r_ref | Reference rate based on network congestion | | r_send | Sending rate | | r_recv | Receiving rate | | r_vin | Target rate for video encoder | | r_vout | Output rate from video encoder | | d_base | Estimated baseline delay | | d_fwd | Measured and filtered one-way delay | | d_queue | Estimated queueing delay | | d_tilde | Equivalent delay after non-linear warping | | p_mark | Estimated packet ECN marking ratio | | p_loss | Estimated packet loss ratio | | x_curr | Aggregate congestion signal | | x_prev | Previous value of aggregate congestion signal | | x_diff | Change in aggregate congestion signal w.r.t. | | | its previous value: x_diff = x_curr - x_prev | | rmode | Rate update mode: (0 = accelerated ramp-up; | | | 1 = gradual update) | | gamma | Rate increase multiplier in accelerated ramp-up | | | mode | | rtt | Estimated round-trip-time at sender | | buffer_len | Rate shaping buffer occupancy measured in bytes | +--------------+-------------------------------------------------+ Figure 2: List of variables. Zhu, et al. Expires September 19, 2016 [Page 6] Internet-Draft NADA March 2016 +---------------+---------------------------------+----------------+ | Notation | Parameter Name | Default Value | +--------------+----------------------------------+----------------+ | PRIO | Weight of priority of the flow | 1.0 | RMIN | Minimum rate of application | 150 Kbps | | | supported by media encoder | | | RMAX | Maximum rate of application | 1.5 Mbps | | | supported by media encoder | | | XREF | Reference congestion level | 20ms | | KAPPA | Scaling parameter for gradual | 0.5 | | | rate update calculation | | | ETA | Scaling parameter for gradual | 2.0 | | | rate update calculation | | | TAU | Upper bound of RTT in gradual | 500ms | | | rate update calculation | | | DELTA | Target feedback interval | 100ms | | DFILT | Bound on filtering delay | 120ms | | LOGWIN | Observation window in time for | 500ms | | | calculating packet summary | | | | statistics at receiver | | | QEPS | Threshold for determining queuing| 10ms | | | delay build up at receiver | | +..............+..................................+................+ | QTH | Delay threshold for non-linear | 50ms | | | warping | | | QMAX | Delay upper bound for non-linear | 400ms | | | warping | | | DLOSS | Delay penalty for loss | 1.0s | | DMARK | Delay penalty for ECN marking | 200ms | +..............+..................................+................+ | GAMMA_MAX | Upper bound on rate increase | 50% | | | ratio for accelerated ramp-up | | | QBOUND | Upper bound on self-inflicted | 50ms | | | queuing delay during ramp up | | +..............+..................................+................+ | FPS | Frame rate of incoming video | 30 | | BETA_S | Scaling parameter for modulating | 0.1 | | | outgoing sending rate | | | BETA_V | Scaling parameter for modulating | 0.1 | | | video encoder target rate | | | ALPHA | Smoothing factor in exponential | 0.1 | | | smoothing of packet loss and | | | | marking ratios | +--------------+----------------------------------+----------------+ Figure 3: List of algorithm parameters. Zhu, et al. Expires September 19, 2016 [Page 7] Internet-Draft NADA March 2016 4.2. Receiver-Side Algorithm The receiver-side algorithm can be outlined as below: On initialization: set d_base = +INFINITY set p_loss = 0 set p_mark = 0 set r_recv = 0 set both t_last and t_curr as current time On receiving a media packet: obtain current timestamp t_curr from system clock obtain from packet header sending time stamp t_sent obtain one-way delay measurement: d_fwd = t_curr - t_sent update baseline delay: d_base = min(d_base, d_fwd) update queuing delay: d_queue = d_fwd - d_base update packet loss ratio estimate p_loss update packet marking ratio estimate p_mark update measurement of receiving rate r_recv On time to send a new feedback report (t_curr - t_last > DELTA): calculate non-linear warping of delay d_tilde if packet loss exists calculate current aggregate congestion signal x_curr determine mode of rate adaptation for sender: rmode send RTCP feedback report containing values of: rmode, x_curr, and r_recv update t_last = t_curr In order for a delay-based flow to hold its ground when competing against loss-based flows (e.g., loss-based TCP), it is important to distinguish between different levels of observed queuing delay. For instance, a moderate queuing delay value below 100ms is likely self- inflicted or induced by other delay-based flows, whereas a high queuing delay value of several hundreds of milliseconds may indicate the presence of a loss-based flow that does not refrain from increased delay. When packet losses are observed, the estimated queuing delay follows a non-linear warping inspired by the delay-adaptive congestion window backoff policy in [Budzisz-TON11]: Zhu, et al. Expires September 19, 2016 [Page 8] Internet-Draft NADA March 2016 / d_queue, if d_queue |||||||||=================> +----------+ -----------+ RTP packets Rate Shaping Buffer Figure 4: NADA Sender Structure 5.2.1. Rate shaping buffer The operation of the live video encoder is out of the scope of the design for the congestion control scheme in NADA. Instead, its behavior is treated as a black box. A rate shaping buffer is employed to absorb any instantaneous mismatch between encoder rate output r_vout and regulated sending rate r_send. Its current level of occupancy is measured in bytes and is denoted as buffer_len. A large rate shaping buffer contributes to higher end-to-end delay, which may harm the performance of real-time media communications. Therefore, the sender has a strong incentive to prevent the rate shaping buffer from building up. The mechanisms adopted are: o To deplete the rate shaping buffer faster by increasing the sending rate r_send; and o To limit incoming packets of the rate shaping buffer by reducing the video encoder target rate r_vin. Zhu, et al. Expires September 19, 2016 [Page 14] Internet-Draft NADA March 2016 5.2.2. Adjusting video target rate and sending rate The target rate for the live video encoder deviates from the network congestion control rate r_ref based on the level of occupancy in the rate shaping buffer: r_vin = r_ref - BETA_V*8*buffer_len*FPS. (11) The actual sending rate r_send is regulated in a similar fashion: r_send = r_ref + BETA_S*8*buffer_len*FPS. (12) In (11) and (12), the first term indicates the rate calculated from network congestion feedback alone. The second term indicates the influence of the rate shaping buffer. A large rate shaping buffer nudges the encoder target rate slightly below -- and the sending rate slightly above -- the reference rate r_ref. Intuitively, the amount of extra rate offset needed to completely drain the rate shaping buffer within the duration of a single video frame is given by 8*buffer_len*FPS, where FPS stands for the frame rate of the video. The scaling parameters BETA_V and BETA_S can be tuned to balance between the competing goals of maintaining a small rate shaping buffer and deviating from the reference rate point. 5.3. Feedback Message Requirements The following list of information is required for NADA congestion control to function properly: o Recommended rate adaptation mode (rmode): a 1-bit flag indicating whether the sender should operate in accelerated ramp-up mode (rmode=0) or gradual update mode (rmode=1). o Aggregated congestion signal (x_curr): the most recently updated value, calculated by the receiver according to Section 4.2. This information is expressed with a unit of 100 microsecond (i.e., 1/10 of a millisecond) in 15 bits. This allows a maximum value of x_curr at approximately 3.27 second. o Receiving rate (r_recv): the most recently measured receiving rate according to Section 5.1.3. This information is expressed with a unit of 10 Kilobits per second (Kbps) in 16 bits. This allows a maximum rate of approximately 6.55Mbps. The above list of information can be accommodated by 32 bits in total. Choice of the feedback message interval DELTA is discussed in Section 6.3 A target feedback interval of DELTA=100ms is recommended. Zhu, et al. Expires September 19, 2016 [Page 15] Internet-Draft NADA March 2016 6. Discussions and Further Investigations 6.1. Choice of delay metrics The current design works with relative one-way-delay (OWD) as the main indication of congestion. The value of the relative OWD is obtained by maintaining the minimum value of observed OWD over a relatively long time horizon and subtract that out from the observed absolute OWD value. Such an approach cancels out the fixed difference between the sender and receiver clocks. It has been widely adopted by other delay-based congestion control approaches such as [RFC6817]. As discussed in [RFC6817], the time horizon for tracking the minimum OWD needs to be chosen with care: it must be long enough for an opportunity to observe the minimum OWD with zero standing queue along the path, and sufficiently short so as to timely reflect "true" changes in minimum OWD introduced by route changes and other rare events. The potential drawback in relying on relative OWD as the congestion signal is that when multiple flows share the same bottleneck, the flow arriving late at the network experiencing a non-empty queue may mistakenly consider the standing queuing delay as part of the fixed path propagation delay. This will lead to slightly unfair bandwidth sharing among the flows. Alternatively, one could move the per-packet statistical handling to the sender instead and use relative round-trip-time (RTT) in lieu of relative OWD, assuming that per-packet acknowledgements are available. The main drawback of RTT-based approach is the noise in the measured delay in the reverse direction. Note that the choice of either delay metric (relative OWD vs. RTT) involves no change in the proposed rate adaptation algorithm. Therefore, comparing the pros and cons regarding which delay metric to adopt can be kept as an orthogonal direction of investigation. 6.2. Method for delay, loss, and marking ratio estimation Like other delay-based congestion control schemes, performance of NADA depends on the accuracy of its delay measurement and estimation module. Appendix A in [RFC6817] provides an extensive discussion on this aspect. The current recommended practice of simply applying a 15-tab minimum filter suffices in guarding against processing delay outliers observed in wired connections. For wireless connections with a higher packet delay variation (PDV), more sophisticated techniques on de-noising, outlier rejection, and trend analysis may be needed. Zhu, et al. Expires September 19, 2016 [Page 16] Internet-Draft NADA March 2016 More sophisticated methods in packet loss ratio calculation, such as that adopted by [Floyd-CCR00], will likely be beneficial. These alternatives are currently under investigation. 6.3. Impact of parameter values In the gradual rate update mode, the parameter TAU indicates the upper bound of round-trip-time (RTT) in feedback control loop. Typically, the observed feedback interval delta is close to the target feedback interval DELTA, and the relative ratio of delta/TAU versus ETA dictates the relative strength of influence from the aggregate congestion signal offset term (x_offset) versus its recent change (x_diff), respectively. These two terms are analogous to the integral and proportional terms in a proportional-integral (PI) controller. The recommended choice of TAU=500ms, DELTA=100ms and ETA = 2.0 corresponds to a relative ratio of 1:10 between the gains of the integral and proportional terms. Consequently, the rate adaptation is mostly driven by the change in the congestion signal with a long-term shift towards its equilibrium value driven by the offset term. Finally, the scaling parameter KAPPA determines the overall speed of the adaptation and needs to strike a balance between responsiveness and stability. The choice of the target feedback interval DELTA needs to strike the right balance between timely feedback and low RTCP feedback message counts. A target feedback interval of DELTA=100ms is recommended, corresponding to a feedback bandwidth of 16Kbps with 200 bytes per feedback message --- less than 0.1% overhead for a 1 Mbps flow. Furthermore, both simulation studies and frequency-domain analysis have established that a feedback interval below 250ms will not break up the feedback control loop of NADA congestion control. In calculating the non-linear warping of delay in (1), the current design uses fixed values of QTH and QMAX. It is possible to adapt the value of both based on past observations of queuing delay in the presence of packet losses. In calculating the aggregate congestion signal x_curr, the choice of DMARK and DLOSS influence the steady-state packet loss/marking ratio experienced by the flow at a given available bandwidth. Higher values of DMARK and DLOSS result in lower steady-state loss/marking ratios, but are more susceptible to the impact of individual packet loss/marking events. While the value of DMARK and DLOSS are fixed and predetermined in the current design, a scheme for automatically tuning these values based on desired bandwidth sharing behavior in the presence of other competing loss-based flows (e.g., loss-based TCP) is under investigation. Zhu, et al. Expires September 19, 2016 [Page 17] Internet-Draft NADA March 2016 [Editor's note: Choice of start value: is this in scope of congestion control, or should this be decided by the application?] 6.4. Sender-based vs. receiver-based calculation In the current design, the aggregated congestion signal x_curr is calculated at the receiver, keeping the sender operation completely independent of the form of actual network congestion indications (delay, loss, or marking). Alternatively, one can move the logics of (1) and (2) to the sender. Such an approach requires slightly higher overhead in the feedback messages, which should contain individual fields on queuing delay (d_queue), packet loss ratio (p_loss), packet marking ratio (p_mark), receiving rate (r_recv), and recommended rate adaptation mode (rmode). 6.5. Incremental deployment One nice property of NADA is the consistent video endpoint behavior irrespective of network node variations. This facilitates gradual, incremental adoption of the scheme. To start off with, the proposed congestion control mechanism can be implemented without any explicit support from the network, and relies solely on observed one-way delay measurements and packet loss ratios as implicit congestion signals. When ECN is enabled at the network nodes with RED-based marking, the receiver can fold its observations of ECN markings into the calculation of the equivalent delay. The sender can react to these explicit congestion signals without any modification. Ultimately, networks equipped with proactive marking based on token bucket level metering can reap the additional benefits of zero standing queues and lower end-to-end delay and work seamlessly with existing senders and receivers. 7. Implementation Status The NADA scheme has been implemented in [ns-2] and [ns-3] simulation platforms. Extensive ns-2 simulation evaluations of an earlier version of the draft are documented in [Zhu-PV13]. Evaluation results of the current draft over several test cases in [I-D.ietf-rmcat-eval-test] have been presented at recent IETF meetings [IETF-90][IETF-91]. Evaluation results of the current draft over several test cases in [I-D.ietf-rmcat-wireless-tests] have been presented at [IETF-93]. Zhu, et al. Expires September 19, 2016 [Page 18] Internet-Draft NADA March 2016 The scheme has also been implemented and evaluated in a lab setting as described in [IETF-90]. Preliminary evaluation results of NADA in single-flow and multi-flow scenarios have been presented in [IETF-91]. 8. IANA Considerations This document makes no request of IANA. 9. Acknowledgements The authors would like to thank Randell Jesup, Luca De Cicco, Piers O'Hanlon, Ingemar Johansson, Stefan Holmer, Cesar Ilharco Magalhaes, Safiqul Islam, Mirja Kuhlewind, and Karen Elisabeth Egede Nielsen for their valuable questions and comments on earlier versions of this draft. 10. References 10.1. Normative References [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, DOI 10.17487/RFC2119, March 1997, . [RFC3168] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition of Explicit Congestion Notification (ECN) to IP", RFC 3168, DOI 10.17487/RFC3168, September 2001, . [RFC3550] Schulzrinne, H., Casner, S., Frederick, R., and V. Jacobson, "RTP: A Transport Protocol for Real-Time Applications", STD 64, RFC 3550, DOI 10.17487/RFC3550, July 2003, . [RFC6679] Westerlund, M., Johansson, I., Perkins, C., O'Hanlon, P., and K. Carlberg, "Explicit Congestion Notification (ECN) for RTP over UDP", RFC 6679, DOI 10.17487/RFC6679, August 2012, . [I-D.ietf-rmcat-eval-test] Sarker, Z., Varun, V., Zhu, X., and M. Ramalho, "Test Cases for Evaluating RMCAT Proposals", draft-ietf-rmcat- eval-test-03 (work in progress), March 2016. Zhu, et al. Expires September 19, 2016 [Page 19] Internet-Draft NADA March 2016 [I-D.ietf-rmcat-cc-requirements] Jesup, R. and Z. Sarker, "Congestion Control Requirements for Interactive Real-Time Media", draft-ietf-rmcat-cc- requirements-09 (work in progress), December 2014. [I-D.ietf-rmcat-video-traffic-model] Zhu, X., Cruz, S., and Z. Sarker, "Modeling Video Traffic Sources for RMCAT Evaluations", draft-ietf-rmcat-video- traffic-model-00 (work in progress), January 2016. [I-D.ietf-rmcat-cc-codec-interactions] Zanaty, M., Singh, V., Nandakumar, S., and Z. Sarker, "Congestion Control and Codec interactions in RTP Applications", draft-ietf-rmcat-cc-codec-interactions-01 (work in progress), October 2015. [I-D.ietf-rmcat-wireless-tests] Sarker, Z., Johansson, I., Zhu, X., Fu, J., Tan, W., and M. Ramalho, "Evaluation Test Cases for Interactive Real- Time Media over Wireless Networks", draft-ietf-rmcat- wireless-tests-01 (work in progress), November 2015. 10.2. Informative References [RFC2309] Braden, B., Clark, D., Crowcroft, J., Davie, B., Deering, S., Estrin, D., Floyd, S., Jacobson, V., Minshall, G., Partridge, C., Peterson, L., Ramakrishnan, K., Shenker, S., Wroclawski, J., and L. Zhang, "Recommendations on Queue Management and Congestion Avoidance in the Internet", RFC 2309, DOI 10.17487/RFC2309, April 1998, . [RFC5348] Floyd, S., Handley, M., Padhye, J., and J. Widmer, "TCP Friendly Rate Control (TFRC): Protocol Specification", RFC 5348, DOI 10.17487/RFC5348, September 2008, . [RFC6660] Briscoe, B., Moncaster, T., and M. Menth, "Encoding Three Pre-Congestion Notification (PCN) States in the IP Header Using a Single Diffserv Codepoint (DSCP)", RFC 6660, DOI 10.17487/RFC6660, July 2012, . [RFC6817] Shalunov, S., Hazel, G., Iyengar, J., and M. Kuehlewind, "Low Extra Delay Background Transport (LEDBAT)", RFC 6817, DOI 10.17487/RFC6817, December 2012, . Zhu, et al. Expires September 19, 2016 [Page 20] Internet-Draft NADA March 2016 [Floyd-CCR00] Floyd, S., Handley, M., Padhye, J., and J. Widmer, "Equation-based Congestion Control for Unicast Applications", ACM SIGCOMM Computer Communications Review vol. 30, no. 4, pp. 43-56, October 2000. [Budzisz-TON11] Budzisz, L., Stanojevic, R., Schlote, A., Baker, F., and R. Shorten, "On the Fair Coexistence of Loss- and Delay- Based TCP", IEEE/ACM Transactions on Networking vol. 19, no. 6, pp. 1811-1824, December 2011. [Zhu-PV13] Zhu, X. and R. Pan, "NADA: A Unified Congestion Control Scheme for Low-Latency Interactive Video", in Proc. IEEE International Packet Video Workshop (PV'13) San Jose, CA, USA, December 2013. [ns-2] "The Network Simulator - ns-2", . [ns-3] "The Network Simulator - ns-3", . [IETF-90] Zhu, X., Ramalho, M., Ganzhorn, C., Jones, P., and R. Pan, "NADA Update: Algorithm, Implementation, and Test Case Evalua6on Results", July 2014, . [IETF-91] Zhu, X., Pan, R., Ramalho, M., Mena, S., Ganzhorn, C., Jones, P., and S. D'Aronco, "NADA Algorithm Update and Test Case Evaluations", November 2014, . [IETF-93] Zhu, X., Pan, R., Ramalho, M., Mena, S., Ganzhorn, C., Jones, P., D'Aronco, S., and J. Fu, "Updates on NADA", July 2015, . Appendix A. Network Node Operations NADA can work with different network queue management schemes and does not assume any specific network node operation. As an example, this appendix describes three variants of queue management behavior at the network node, leading to either implicit or explicit congestion signals. Zhu, et al. Expires September 19, 2016 [Page 21] Internet-Draft NADA March 2016 In all three flavors described below, the network queue operates with the simple first-in-first-out (FIFO) principle. There is no need to maintain per-flow state. The system can scale easily with a large number of video flows and at high link capacity. A.1. Default behavior of drop tail queues In a conventional network with drop tail or RED queues, congestion is inferred from the estimation of end-to-end delay and/or packet loss. Packet drops at the queue are detected at the receiver, and contributes to the calculation of the aggregated congestion signal x_curr. No special action is required at network node. A.2. RED-based ECN marking In this mode, the network node randomly marks the ECN field in the IP packet header following the Random Early Detection (RED) algorithm [RFC2309]. Calculation of the marking probability involves the following steps: on packet arrival: update smoothed queue size q_avg as: q_avg = w*q + (1-w)*q_avg. calculate marking probability p as: / 0, if q < q_lo; | | q_avg - q_lo p= < p_max*--------------, if q_lo <= q < q_hi; | q_hi - q_lo | \ p = 1, if q >= q_hi. Here, q_lo and q_hi corresponds to the low and high thresholds of queue occupancy. The maximum marking probability is p_max. The ECN markings events will contribute to the calculation of an equivalent delay x_curr at the receiver. No changes are required at the sender. A.3. Random Early Marking with Virtual Queues Advanced network nodes may support random early marking based on a token bucket algorithm originally designed for Pre-Congestion Notification (PCN) [RFC6660]. The early congestion notification (ECN) bit in the IP header of packets are marked randomly. The marking probability is calculated based on a token-bucket algorithm Zhu, et al. Expires September 19, 2016 [Page 22] Internet-Draft NADA March 2016 originally designed for the Pre-Congestion Notification (PCN) [RFC6660]. The target link utilization is set as 90%; the marking probability is designed to grow linearly with the token bucket size when it varies between 1/3 and 2/3 of the full token bucket limit. * upon packet arrival, meter packet against token bucket (r,b); * update token level b_tk; * calculate the marking probability as: / 0, if b-b_tk < b_lo; | | b-b_tk-b_lo p = < p_max* --------------, if b_lo<= b-b_tk =b_hi. Here, the token bucket lower and upper limits are denoted by b_lo and b_hi, respectively. The parameter b indicates the size of the token bucket. The parameter r is chosen to be below capacity, resulting in slight under-utilization of the link. The maximum marking probability is p_max. The ECN markings events will contribute to the calculation of an equivalent delay x_curr at the receiver. No changes are required at the sender. The virtual queuing mechanism from the PCN-based marking algorithm will lead to additional benefits such as zero standing queues. Authors' Addresses Xiaoqing Zhu Cisco Systems 12515 Research Blvd., Building 4 Austin, TX 78759 USA Email: xiaoqzhu@cisco.com Zhu, et al. Expires September 19, 2016 [Page 23] Internet-Draft NADA March 2016 Rong Pan Cisco Systems 3625 Cisco Way San Jose, CA 95134 USA Email: ropan@cisco.com Michael A. Ramalho Cisco Systems, Inc. 8000 Hawkins Road Sarasota, FL 34241 USA Phone: +1 919 476 2038 Email: mramalho@cisco.com Sergio Mena de la Cruz Cisco Systems EPFL, Quartier de l'Innovation, Batiment E Ecublens, Vaud 1015 Switzerland Email: semena@cisco.com Paul E. Jones Cisco Systems 7025 Kit Creek Rd. Research Triangle Park, NC 27709 USA Email: paulej@packetizer.com Jiantao Fu Cisco Systems 707 Tasman Drive Milpitas, CA 95035 USA Email: jianfu@cisco.com Zhu, et al. Expires September 19, 2016 [Page 24] Internet-Draft NADA March 2016 Stefano D'Aronco Ecole Polytechnique Federale de Lausanne EPFL STI IEL LTS4, ELD 220 (Batiment ELD), Station 11 Lausanne CH-1015 Switzerland Email: stefano.daronco@epfl.ch Charles Ganzhorn 7900 International Drive, International Plaza, Suite 400 Bloomington, MN 55425 USA Email: charles.ganzhorn@gmail.com Zhu, et al. Expires September 19, 2016 [Page 25]