path: root/doc/rfc/rfc8869.txt

Internet Engineering Task Force (IETF)                         Z. Sarker
Request for Comments: 8869                                   Ericsson AB
Category: Informational                                           X. Zhu
ISSN: 2070-1721                                                    J. Fu
                                                           Cisco Systems
                                                            January 2021


  Evaluation Test Cases for Interactive Real-Time Media over Wireless
                                Networks

Abstract

   The Real-time Transport Protocol (RTP) is a common transport choice
   for interactive multimedia communication applications.  The
   performance of these applications typically depends on a well-
   functioning congestion control algorithm.  To ensure a seamless and
   robust user experience, a well-designed RTP-based congestion control
   algorithm should work well across all access network types.  This
   document describes test cases for evaluating performances of
   candidate congestion control algorithms over cellular and Wi-Fi
   networks.

Status of This Memo

   This document is not an Internet Standards Track specification; it is
   published for informational purposes.

   This document is a product of the Internet Engineering Task Force
   (IETF).  It represents the consensus of the IETF community.  It has
   received public review and has been approved for publication by the
   Internet Engineering Steering Group (IESG).  Not all documents
   approved by the IESG are candidates for any level of Internet
   Standard; see Section 2 of RFC 7841.

   Information about the current status of this document, any errata,
   and how to provide feedback on it may be obtained at
   https://www.rfc-editor.org/info/rfc8869.

Copyright Notice

   Copyright (c) 2021 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
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   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
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   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
   2.  Cellular Network Specific Test Cases
     2.1.  Varying Network Load
       2.1.1.  Network Connection
       2.1.2.  Simulation Setup
       2.1.3.  Expected Behavior
     2.2.  Bad Radio Coverage
       2.2.1.  Network Connection
       2.2.2.  Simulation Setup
       2.2.3.  Expected Behavior
     2.3.  Desired Evaluation Metrics for Cellular Test Cases
   3.  Wi-Fi Networks Specific Test Cases
     3.1.  Bottleneck in Wired Network
       3.1.1.  Network Topology
       3.1.2.  Test/Simulation Setup
       3.1.3.  Typical Test Scenarios
       3.1.4.  Expected Behavior
     3.2.  Bottleneck in Wi-Fi Network
       3.2.1.  Network Topology
       3.2.2.  Test/Simulation Setup
       3.2.3.  Typical Test Scenarios
       3.2.4.  Expected Behavior
     3.3.  Other Potential Test Cases
       3.3.1.  EDCA/WMM usage
       3.3.2.  Effect of Heterogeneous Link Rates
   4.  IANA Considerations
   5.  Security Considerations
   6.  References
     6.1.  Normative References
     6.2.  Informative References
   Contributors
   Acknowledgments
   Authors' Addresses

1.  Introduction

   Wireless networks (both cellular and Wi-Fi [IEEE802.11]) are an
   integral and increasingly more significant part of the Internet.
   Typical application scenarios for interactive multimedia
   communication over wireless include video conferencing calls in a bus
   or train as well as live media streaming at home.  It is well known
   that the characteristics and technical challenges for supporting
   multimedia services over wireless are very different from those of
   providing the same service over a wired network.  Although the basic
   test cases as defined in [RFC8867] have covered many common effects
   of network impairments for evaluating RTP-based congestion control
   schemes, they remain to be tested over characteristics and dynamics
   unique to a given wireless environment.  For example, in cellular
   networks, the base station maintains individual queues per radio
   bearer per user hence it leads to a different nature of interactions
   between traffic flows of different users.  This contrasts with a
   typical wired network setting where traffic flows from all users
   share the same queue at the bottleneck.  Furthermore, user mobility
   patterns in a cellular network differ from those in a Wi-Fi network.
   Therefore, it is important to evaluate the performance of proposed
   candidate RTP-based congestion control solutions over cellular mobile
   networks and over Wi-Fi networks respectively.

   [RFC8868] provides guidelines for evaluating candidate algorithms and
   recognizes the importance of testing over wireless access networks.
   However, it does not describe any specific test cases for performance
   evaluation of candidate algorithms.  This document describes test
   cases specifically targeting cellular and Wi-Fi networks.

2.  Cellular Network Specific Test Cases

   A cellular environment is more complicated than its wireline
   counterpart since it seeks to provide services in the context of
   variable available bandwidth, location dependencies, and user
   mobilities at different speeds.  In a cellular network, the user may
   reach the cell edge, which may lead to a significant number of
   retransmissions to deliver the data from the base station to the
   destination and vice versa.  These radio links will often act as a
   bottleneck for the rest of the network and will eventually lead to
   excessive delays or packet drops.  An efficient retransmission or
   link adaptation mechanism can reduce the packet loss probability, but
   some packet losses and delay variations will remain.  Moreover, with
   increased cell load or handover to a congested cell, congestion in
   the transport network will become even worse.  Besides, there exist
   certain characteristics that distinguish the cellular network from
   other wireless access networks such as Wi-Fi.  In a cellular network:

   *  The bottleneck is often a shared link with relatively few users.

      -  The cost per bit over the shared link varies over time and is
         different for different users.

      -  Leftover/unused resources can be consumed by other greedy
         users.

   *  Queues are always per radio bearer, hence each user can have many
      such queues.

   *  Users can experience both inter- and intra-Radio Access Technology
      (RAT) handovers (see [HO-def-3GPP] for the definition of
      "handover").

   *  Handover between cells or change of serving cells (as described in
      [HO-LTE-3GPP] and [HO-UMTS-3GPP]) might cause user plane
      interruptions, which can lead to bursts of packet losses, delay,
      and/or jitter.  The exact behavior depends on the type of radio
      bearer.  Typically, the default best-effort bearers do not
      generate packet loss, instead, packets are queued up and
      transmitted once the handover is completed.

   *  The network part decides how much the user can transmit.

   *  The cellular network has variable link capacity per user.

      -  It can vary as fast as a period of milliseconds.

      -  It depends on many factors (such as distance, speed,
         interference, different flows).

      -  It uses complex and smart link adaptation, which makes the link
         behavior ever more dynamic.

      -  The scheduling priority depends on the estimated throughput.

   *  Both Quality of Service (QoS) and non-QoS radio bearers can be
      used.

   Hence, a real-time communication application operating over a
   cellular network needs to cope with a shared bottleneck link and
   variable link capacity, events like handover, non-congestion-related
   loss, and abrupt changes in bandwidth (both short term and long term)
   due to handover, network load, and bad radio coverage.  Even though
   3GPP has defined QoS bearers [QoS-3GPP] to ensure high-quality user
   experience, it is still preferable for real-time applications to
   behave in an adaptive manner.

   Different mobile operators deploy their own cellular networks with
   their own set of network functionalities and policies.  Usually, a
   mobile operator network includes a range of radio access technologies
   such as 3G and 4G/LTE.  Looking at the specifications of such radio
   technologies, it is evident that only the more recent radio
   technologies can support the high bandwidth requirements from real-
   time interactive video applications.  Future real-time interactive
   applications will impose even greater demand on cellular network
   performance, which makes 4G (and beyond) radio technologies more
   suitable for such genre of application.

   The key factors in defining test cases for cellular networks are:

   *  Shared and varying link capacity

   *  Mobility

   *  Handover

   However, these factors are typically highly correlated in a cellular
   network.  Therefore, instead of devising separate test cases for
   individual important events, we have divided the test cases into two
   categories.  It should be noted that the goal of the following test
   cases is to evaluate the performance of candidate algorithms over the
   radio interface of the cellular network.  Hence, it is assumed that
   the radio interface is the bottleneck link between the communicating
   peers and that the core network does not introduce any extra
   congestion along the path.  Consequently, this document has left out
   of scope the combination of multiple access technologies involving
   both cellular and Wi-Fi users.  In this latter case, the shared
   bottleneck is likely at the wired backhaul link.  These test cases
   further assume a typical real-time telephony scenario where one real-
   time session consists of one voice stream and one video stream.

   Even though it is possible to carry out tests over operational
   cellular networks (e.g., LTE/5G), and actually such tests are already
   available today, these tests cannot in general be carried out in a
   deterministic fashion to ensure repeatability.  The main reason is
   that these networks are controlled by cellular operators, and there
   exists various amounts of competing traffic in the same cell(s).  In
   practice, it is only in underground mines that one can carry out near
   deterministic testing.  Even there, it is not guaranteed either as
   workers in the mines may carry with them their personal mobile
   phones.  Furthermore, the underground mining setting may not reflect
   typical usage patterns in an urban setting.  We, therefore, recommend
   that a cellular network simulator be used for the test cases defined
   in this document, for example -- the LTE simulator in [NS-3].

2.1.  Varying Network Load

   The goal of this test is to evaluate the performance of the candidate
   congestion control algorithm under varying network load.  The network
   load variation is created by adding and removing network users,
   a.k.a.  User Equipment (UE), during the simulation.  In this test
   case, each user/UE in the media session is an endpoint following RTP-
   based congestion control.  User arrivals follow a Poisson
   distribution proportional to the length of the call, to keep the
   number of users per cell fairly constant during the evaluation
   period.  At the beginning of the simulation, there should be enough
   time to warm up the network.  This is to avoid running the evaluation
   in an empty network where network nodes have empty buffers and low
   interference at the beginning of the simulation.  This network
   initialization period should be excluded from the evaluation period.
   Typically, the evaluation period starts 30 seconds after test
   initialization.

   This test case also includes user mobility and some competing
   traffic.  The latter includes both the same types of flows (with same
   adaptation algorithms) and different types of flows (with different
   services and congestion control schemes).

2.1.1.  Network Connection

   Each mobile user is connected to a fixed user.  The connection
   between the mobile user and fixed user consists of a cellular radio
   access, an Evolved Packet Core (EPC), and an Internet connection.
   The mobile user is connected to the EPC using cellular radio access
   technology, which is further connected to the Internet.  At the other
   end, the fixed user is connected to the Internet via a wired
   connection with sufficiently high bandwidth, for instance, 10 Gbps,
   so that the system bottleneck is on the cellular radio access
   interface.  The wired connection in this setup does not introduce any
   network impairments to the test; it only adds 10 ms of one-way
   propagation delay.

   The path from the fixed user to the mobile users is defined as
   "downlink", and the path from the mobile users to the fixed user is
   defined as "uplink".  We assume that only uplink or downlink is
   congested for mobile users.  Hence, we recommend that the uplink and
   downlink simulations are run separately.

                             uplink
            ++)))        +-------------------------->
            ++-+      ((o))
            |  |       / \     +-------+     +------+    +---+
            +--+      /   \----+       +-----+      +----+   |
                     /     \   +-------+     +------+    +---+
             UE         BS        EPC        Internet    fixed
                         <--------------------------+
                                  downlink

                       Figure 1: Simulation Topology

2.1.2.  Simulation Setup

   The values enclosed within "[ ]" for the following simulation
   attributes follow the same notion as in [RFC8867].  The desired
   simulation setup is as follows:

   Radio environment:

      Deployment and propagation model:  3GPP case 1 (see
         [HO-deploy-3GPP])

      Antenna:  Multiple-Input and Multiple-Output (MIMO), 2D or 3D
         antenna pattern

      Mobility:  [3 km/h, 30 km/h]

      Transmission bandwidth:  10 MHz

      Number of cells:  multi-cell deployment (3 cells per Base Station
         (BS) * 7 BS) = 21 cells

      Cell radius:  166.666 meters

      Scheduler:  Proportional fair with no priority

      Bearer:  Default bearer for all traffic

      Active Queue Management (AQM) settings:  AQM [on, off]

   End-to-end Round Trip Time (RTT):  [40 ms, 150 ms]

   User arrival model:  Poisson arrival model

   User intensity:

      Downlink user intensity:  {0.7, 1.4, 2.1, 2.8, 3.5, 4.2, 4.9, 5.6,
         6.3, 7.0, 7.7, 8.4, 9,1, 9.8, 10.5}

      Uplink user intensity:  {0.7, 1.4, 2.1, 2.8, 3.5, 4.2, 4.9, 5.6,
         6.3, 7.0}

   Simulation duration:  91 s

   Evaluation period:  30 s - 60 s

   Media traffic:

      Media type:  Video

         Media direction:  [uplink, downlink]

         Number of media sources per user:  One (1)

         Media duration per user:  30 s

         Media source:  same as defined in Section 4.3 of [RFC8867]

      Media type:  Audio

         Media direction:  [uplink, downlink]

         Number of media sources per user:  One (1)

         Media duration per user:  30 s

         Media codec:  Constant Bit Rate (CBR)

         Media bitrate:  20 Kbps

         Adaptation:  off

   Other traffic models:

      Downlink simulation:  Maximum of 4 Mbps/cell (web browsing or FTP
         traffic following default TCP congestion control [RFC5681])

      Uplink simulation:  Maximum of 2 Mbps/cell (web browsing or FTP
         traffic following default TCP congestion control [RFC5681])

2.1.3.  Expected Behavior

   The investigated congestion control algorithms should result in
   maximum possible network utilization and stability in terms of rate
   variations, lowest possible end-to-end frame latency, network
   latency, and Packet Loss Rate (PLR) at different cell load levels.

2.2.  Bad Radio Coverage

   The goal of this test is to evaluate the performance of the candidate
   congestion control algorithm when users visit part of the network
   with bad radio coverage.  The scenario is created by using a larger
   cell radius than that in the previous test case.  In this test case,
   each user/UE in the media session is an endpoint following RTP-based
   congestion control.  User arrivals follow a Poisson distribution
   proportional to the length of the call, to keep the number of users
   per cell fairly constant during the evaluation period.  At the
   beginning of the simulation, there should be enough time to warm up
   the network.  This is to avoid running the evaluation in an empty
   network where network nodes have empty buffers and low interference
   at the beginning of the simulation.  This network initialization
   period should be excluded from the evaluation period.  Typically, the
   evaluation period starts 30 seconds after test initialization.

   This test case also includes user mobility and some competing
   traffic.  The latter includes the same kind of flows (with same
   adaptation algorithms).

2.2.1.  Network Connection

   Same as defined in Section 2.1.1.

2.2.2.  Simulation Setup

   The desired simulation setup is the same as the Varying Network Load
   test case defined in Section 2.1 except for the following changes:

   Radio environment:  Same as defined in Section 2.1.2 except for the
      following:

      Deployment and propagation model:  3GPP case 3 (see
         [HO-deploy-3GPP])

      Cell radius:  577.3333 meters

      Mobility:  3 km/h

   User intensity:  {0.7, 1.4, 2.1, 2.8, 3.5, 4.2, 4.9, 5.6, 6.3, 7.0}

   Media traffic model:  Same as defined in Section 2.1.2

   Other traffic models:

      Downlink simulation:  Maximum of 2 Mbps/cell (web browsing or FTP
         traffic following default TCP congestion control [RFC5681])

      Uplink simulation:  Maximum of 1 Mbps/cell (web browsing or FTP
         traffic following default TCP congestion control [RFC5681])

2.2.3.  Expected Behavior

   The investigated congestion control algorithms should result in
   maximum possible network utilization and stability in terms of rate
   variations, lowest possible end-to-end frame latency, network
   latency, and Packet Loss Rate (PLR) at different cell load levels.

2.3.  Desired Evaluation Metrics for Cellular Test Cases

   The evaluation criteria document [RFC8868] defines the metrics to be
   used to evaluate candidate algorithms.  Considering the nature and
   distinction of cellular networks, we recommend that at least the
   following metrics be used to evaluate the performance of the
   candidate algorithms:

   *  Average cell throughput (for all cells), shows cell utilization.

   *  Application sending and receiving bitrate, goodput.

   *  Packet Loss Rate (PLR).

   *  End-to-end media frame delay.  For video, this means the delay
      from capture to display.

   *  Transport delay.

   *  Algorithm stability in terms of rate variation.

3.  Wi-Fi Networks Specific Test Cases

   Given the prevalence of Internet access links over Wi-Fi, it is
   important to evaluate candidate RTP-based congestion control
   solutions over test cases that include Wi-Fi access links.  Such
   evaluations should highlight the inherently different characteristics
   of Wi-Fi networks in contrast to their wired counterparts:

   *  The wireless radio channel is subject to interference from nearby
      transmitters, multipath fading, and shadowing.  These effects lead
      to fluctuations in the link throughput and sometimes an error-
      prone communication environment.

   *  Available network bandwidth is not only shared over the air
      between concurrent users but also between uplink and downlink
      traffic due to the half-duplex nature of the wireless transmission
      medium.

   *  Packet transmissions over Wi-Fi are susceptible to contentions and
      collisions over the air.  Consequently, traffic load beyond a
      certain utilization level over a Wi-Fi network can introduce
      frequent collisions over the air and significant network overhead,
      as well as packet drops due to buffer overflow at the
      transmitters.  This, in turn, leads to excessive delay,
      retransmissions, packet losses, and lower effective bandwidth for
      applications.  Note further that the collision-induced delay and
      loss patterns are qualitatively different from those caused by
      congestion over a wired connection.

   *  The IEEE 802.11 standard (i.e., Wi-Fi) supports multi-rate
      transmission capabilities by dynamically choosing the most
      appropriate modulation and coding scheme (MCS) for the given
      received signal strength.  A different choice in the MCS Index
      leads to different physical-layer (PHY-layer) link rates and
      consequently different application-layer throughput.

   *  The presence of legacy devices (e.g., ones operating only in IEEE
      802.11b) at a much lower PHY-layer link rate can significantly
      slow down the rest of a modern Wi-Fi network.  As discussed in
      [Heusse2003], the main reason for such anomaly is that it takes
      much longer to transmit the same packet over a slower link than
      over a faster link, thereby consuming a substantial portion of air
      time.

   *  Handover from one Wi-Fi Access Point (AP) to another may lead to
      excessive packet delays and losses during the process.

   *  IEEE 802.11e has introduced the Enhanced Distributed Channel
      Access (EDCA) mechanism to allow different traffic categories to
      contend for channel access using different random back-off
      parameters.  This mechanism is a mandatory requirement for the Wi-
      Fi Multimedia (WMM) certification in Wi-Fi Alliance.  It allows
      for prioritization of real-time application traffic such as voice
      and video over non-urgent data transmissions (e.g., file
      transfer).

   In summary, the presence of Wi-Fi access links in different network
   topologies can exert different impacts on the network performance in
   terms of application-layer effective throughput, packet loss rate,
   and packet delivery delay.  These, in turn, will influence the
   behavior of end-to-end real-time multimedia congestion control.

   Unless otherwise mentioned, the test cases in this section choose the
   PHY- and MAC-layer parameters based on the IEEE 802.11n standard.
   Statistics collected from enterprise Wi-Fi networks show that the two
   dominant physical modes are 802.11n and 802.11ac, accounting for 41%
   and 58% of connected devices, respectively.  As Wi-Fi standards
   evolve over time -- for instance, with the introduction of the
   emerging Wi-Fi 6 (based on IEEE 802.11ax) products -- the PHY- and
   MAC-layer test case specifications need to be updated accordingly to
   reflect such changes.

   Typically, a Wi-Fi access network connects to a wired infrastructure.
   Either the wired or the Wi-Fi segment of the network can be the
   bottleneck.  The following sections describe basic test cases for
   both scenarios separately.  The same set of performance metrics as in
   [RFC8867]) should be collected for each test case.

   We recommend carrying out the test cases as defined in this document
   using a simulator, such as [NS-2] or [NS-3].  When feasible, it is
   encouraged to perform testbed-based evaluations using Wi-Fi access
   points and endpoints running up-to-date IEEE 802.11 protocols, such
   as 802.11ac and the emerging Wi-Fi 6, so as to verify the viability
   of the candidate schemes.

3.1.  Bottleneck in Wired Network

   The test scenarios below are intended to mimic the setup of video
   conferencing over Wi-Fi connections from the home.  Typically, the
   Wi-Fi home network is not congested, and the bottleneck is present
   over the wired home access link.  Although it is expected that test
   evaluation results from this section are similar to those in
   [RFC8867], it is still worthwhile to run through these tests as
   sanity checks.

3.1.1.  Network Topology

   Figure 2 shows the network topology of Wi-Fi test cases.  The test
   contains multiple mobile nodes (MNs) connected to a common Wi-Fi AP
   and their corresponding wired clients on fixed nodes (FNs).  Each
   connection carries either an RTP-based media flow or a TCP traffic
   flow.  Directions of the flows can be uplink (i.e., from mobile nodes
   to fixed nodes), downlink (i.e., from fixed nodes to mobile nodes),
   or bidirectional.  The total number of uplink/downlink/bidirectional
   flows for RTP-based media traffic and TCP traffic are denoted as N
   and M, respectively.

                                   Uplink
                             +----------------->+
            +------+                                       +------+
            | MN_1 |))))                             /=====| FN_1 |
            +------+    ))                          //     +------+
                .        ))                        //         .
                .         ))                      //          .
                .          ))                    //           .
            +------+         +----+         +-----+        +------+
            | MN_N | ))))))) |    |         |     |========| FN_N |
            +------+         |    |         |     |        +------+
                             | AP |=========| FN0 |
           +----------+      |    |         |     |      +----------+
           | MN_tcp_1 | )))) |    |         |     |======| FN_tcp_1 |
           +----------+      +----+         +-----+      +----------+
                 .          ))                 \\             .
                 .         ))                   \\            .
                 .        ))                     \\           .
           +----------+  ))                       \\     +----------+
           | MN_tcp_M |)))                         \=====| FN_tcp_M |
           +----------+                                  +----------+
                            +<-----------------+
                                    Downlink

              Figure 2: Network Topology for Wi-Fi Test Cases

3.1.2.  Test/Simulation Setup

   Test duration:  120 s

   Wi-Fi network characteristics:

      Radio propagation model:  Log-distance path loss propagation model
         (see [NS3WiFi])

      PHY- and MAC-layer configuration:  IEEE 802.11n

      MCS Index at 11:  Raw data rate at 52 Mbps, 16-QAM (Quadrature
         amplitude modulation) and 1/2 coding rate

   Wired path characteristics:

      Path capacity:  1 Mbps

      One-way propagation delay:  50 ms

      Maximum end-to-end jitter:  30 ms

      Bottleneck queue type:  Drop tail

      Bottleneck queue size:  300 ms

      Path loss ratio:  0%

   Application characteristics:

      Media traffic:

         Media type:  Video

         Media direction:  See Section 3.1.3

         Number of media sources (N):  See Section 3.1.3

         Media timeline:

            Start time:  0 s

            End time:  119 s

      Competing traffic:

         Type of sources:  Long-lived TCP or CBR over UDP

         Traffic direction:  See Section 3.1.3

         Number of sources (M):  See Section 3.1.3

         Congestion control:  Default TCP congestion control [RFC5681]
            or CBR traffic over UDP

         Traffic timeline:  See Section 3.1.3

3.1.3.  Typical Test Scenarios

   Single uplink RTP-based media flow:  N=1 with uplink direction and
      M=0.

   One pair of bidirectional RTP-based media flows:  N=2 (i.e., one
      uplink flow and one downlink flow); M=0.

   One pair of bidirectional RTP-based media flows:  N=2; one uplink on-
      off CBR flow over UDP: M=1 (uplink).  The CBR flow has ON time at
      t=0s-60s and OFF time at t=60s-119s.

   One pair of bidirectional RTP-based media flows:  N=2; one uplink
      off-on CBR flow over UDP: M=1 (uplink).  The CBR flow has OFF time
      at t=0s-60s and ON time at t=60s-119s.

   One RTP-based media flow competing against one long-lived TCP flow
   in the uplink direction:  N=1 (uplink) and M=1 (uplink).  The TCP
      flow has start time at t=0s and end time at t=119s.

3.1.4.  Expected Behavior

   Single uplink RTP-based media flow:  The candidate algorithm is
      expected to detect the path capacity constraint, to converge to
      the bottleneck link capacity, and to adapt the flow to avoid
      unwanted oscillations when the sending bit rate is approaching the
      bottleneck link capacity.  No excessive oscillations in the media
      rate should be present.

   Bidirectional RTP-based media flows:  The candidate algorithm is
      expected to converge to the bottleneck capacity of the wired path
      in both directions despite the presence of measurement noise over
      the Wi-Fi connection.  In the presence of background TCP or CBR
      over UDP traffic, the rate of RTP-based media flows should adapt
      promptly to the arrival and departure of background traffic flows.

   One RTP-based media flow competing with long-lived TCP flow in the
   uplink direction:  The candidate algorithm is expected to avoid
      congestion collapse and to stabilize at a fair share of the
      bottleneck link capacity.

3.2.  Bottleneck in Wi-Fi Network

   The test cases in this section assume that the wired segment along
   the media path is well-provisioned, whereas the bottleneck exists
   over the Wi-Fi access network.  This is to mimic the application
   scenarios typically encountered by users in an enterprise environment
   or at a coffee house.

3.2.1.  Network Topology

   Same as defined in Section 3.1.1.

3.2.2.  Test/Simulation Setup

   Test duration:  120 s

   Wi-Fi network characteristics:

      Radio propagation model:  Log-distance path loss propagation model
         (see [NS3WiFi])

      PHY- and MAC-layer configuration:  IEEE 802.11n

      MCS Index at 11:  Raw data rate at 52 Mbps, 16-QAM (Quadrature
         amplitude modulation) and 1/2 coding rate

   Wired path characteristics:

      Path capacity:  100 Mbps

      One-Way propagation delay:  50 ms

      Maximum end-to-end jitter:  30 ms

      Bottleneck queue type:  Drop tail

      Bottleneck queue size:  300 ms

      Path loss ratio:  0%

   Application characteristics

      Media traffic:

         Media type:  Video

         Media direction:  See Section 3.2.3

         Number of media sources (N):  See Section 3.2.3

         Media timeline:

            Start time:  0 s

            End time:  119 s

      Competing traffic:

         Type of sources:  long-lived TCP or CBR over UDP

         Number of sources (M):  See Section 3.2.3

         Traffic direction:  See Section 3.2.3

         Congestion control:  Default TCP congestion control [RFC5681]
            or CBR traffic over UDP

         Traffic timeline:  See Section 3.2.3

3.2.3.  Typical Test Scenarios

   This section describes a few test scenarios that are deemed as
   important for understanding the behavior of a candidate RTP-based
   congestion control scheme over a Wi-Fi network.

   Multiple RTP-based media flows sharing the wireless downlink:  N=16
      (all downlink); M=0.  This test case is for studying the impact of
      contention on the multiple concurrent media flows.  For an 802.11n
      network, given the MCS Index of 11 and the corresponding link rate
      of 52 Mbps, the total application-layer throughput (assuming
      reasonable distance, low interference, and infrequent contentions
      caused by competing streams) is around 20 Mbps.  A total of N=16
      RTP-based media flows (with a maximum rate of 1.5 Mbps each) are
      expected to saturate the wireless interface in this experiment.
      Evaluation of a given candidate scheme should focus on whether the
      downlink media flows can stabilize at a fair share of the total
      application-layer throughput.

   Multiple RTP-based media flows sharing the wireless uplink:  N=16
      (all uplink); M=0.  When multiple clients attempt to transmit
      media packets uplink over the Wi-Fi network, they introduce more
      frequent contentions and potential collisions.  Per-flow
      throughput is expected to be lower than that in the previous
      downlink-only scenario.  Evaluation of a given candidate scheme
      should focus on whether the uplink flows can stabilize at a fair
      share of the total application-layer throughput.

   Multiple bidirectional RTP-based media flows:  N=16 (8 uplink and 8
      downlink); M=0.  The goal of this test is to evaluate the
      performance of the candidate scheme in terms of bandwidth fairness
      between uplink and downlink flows.

   Multiple bidirectional RTP-based media flows with on-off CBR
   traffic over UDP:  N=16 (8 uplink and 8 downlink); M=5 (uplink).  The
      goal of this test is to evaluate the adaptation behavior of the
      candidate scheme when its available bandwidth changes due to the
      departure of background traffic.  The background traffic consists
      of several (e.g., M=5) CBR flows transported over UDP.  These
      background flows are ON at time t=0-60s and OFF at time t=61-120s.

   Multiple bidirectional RTP-based media flows with off-on CBR
   traffic over UDP:  N=16 (8 uplink and 8 downlink); M=5 (uplink).  The
      goal of this test is to evaluate the adaptation behavior of the
      candidate scheme when its available bandwidth changes due to the
      arrival of background traffic.  The background traffic consists of
      several (e.g., M=5) parallel CBR flows transported over UDP.
      These background flows are OFF at time t=0-60s and ON at times
      t=61-120s.

   Multiple bidirectional RTP-based media flows in the presence of
   background TCP traffic:  N=16 (8 uplink and 8 downlink); M=5
      (uplink).  The goal of this test is to evaluate how RTP-based
      media flows compete against TCP over a congested Wi-Fi network for
      a given candidate scheme.  TCP flows have start time at t=40s and
      end time at t=80s.

   Varying number of RTP-based media flows:  A series of tests can be
      carried out for the above test cases with different values of N,
      e.g., N=[4, 8, 12, 16, 20].  The goal of this test is to evaluate
      how a candidate scheme responds to varying traffic load/demand
      over a congested Wi-Fi network.  The start times of the media
      flows are randomly distributed within a window of t=0-10s; their
      end times are randomly distributed within a window of t=110-120s.

3.2.4.  Expected Behavior

   Multiple downlink RTP-based media flows:  Each media flow is expected
      to get its fair share of the total bottleneck link bandwidth.
      Overall bandwidth usage should not be significantly lower than
      that experienced by the same number of concurrent downlink TCP
      flows.  In other words, the behavior of multiple concurrent TCP
      flows will be used as a performance benchmark for this test
      scenario.  The end-to-end delay and packet loss ratio experienced
      by each flow should be within an acceptable range for real-time
      multimedia applications.

   Multiple uplink RTP-based media flows:  Overall bandwidth usage by
      all media flows should not be significantly lower than that
      experienced by the same number of concurrent uplink TCP flows.  In
      other words, the behavior of multiple concurrent TCP flows will be
      used as a performance benchmark for this test scenario.

   Multiple bidirectional RTP-based media flows with dynamic
   background traffic carrying CBR flows over UDP:  The media flows are
      expected to adapt in a timely fashion to the changes in available
      bandwidth introduced by the arrival/departure of background
      traffic.

   Multiple bidirectional RTP-based media flows with dynamic
   background traffic over TCP:  During the presence of TCP background
      flows, the overall bandwidth usage by all media flows should not
      be significantly lower than those achieved by the same number of
      bidirectional TCP flows.  In other words, the behavior of multiple
      concurrent TCP flows will be used as a performance benchmark for
      this test scenario.  All downlink media flows are expected to
      obtain similar bandwidth as each other.  The throughput of each
      media flow is expected to decrease upon the arrival of TCP
      background traffic and, conversely, increase upon their departure.
      Both reactions should occur in a timely fashion, for example,
      within 10s of seconds.

   Varying number of bidirectional RTP-based media flows:  The test
      results for varying values of N -- while keeping all other
      parameters constant -- is expected to show steady and stable per-
      flow throughput for each value of N.  The average throughput of
      all media flows is expected to stay constant around the maximum
      rate when N is small, then gradually decrease with increasing
      value of N till it reaches the minimum allowed rate, beyond which
      the offered load to the Wi-Fi network exceeds its capacity (i.e.,
      with a very large value of N).

3.3.  Other Potential Test Cases

3.3.1.  EDCA/WMM usage

   The EDCA/WMM mechanism defines prioritized QoS for four traffic
   classes (or Access Categories).  RTP-based real-time media flows
   should achieve better performance in terms of lower delay and fewer
   packet losses with EDCA/WMM enabled when competing against non-
   interactive background traffic such as file transfers.  When most of
   the traffic over Wi-Fi is dominated by media, however, turning on WMM
   may degrade performance since all media flows now attempt to access
   the wireless transmission medium more aggressively, thereby causing
   more frequent collisions and collision-induced losses.  This is a
   topic worthy of further investigation.

3.3.2.  Effect of Heterogeneous Link Rates

   As discussed in [Heusse2003], the presence of clients operating over
   slow PHY-layer link rates (e.g., a legacy 802.11b device) connected
   to a modern network may adversely impact the overall performance of
   the network.  Additional test cases can be devised to evaluate the
   effect of clients with heterogeneous link rates on the performance of
   the candidate congestion control algorithm.  Such test cases, for
   instance, can specify that the PHY-layer link rates for all clients
   span over a wide range (e.g., 2 Mbps to 54 Mbps) for investigating
   its effect on the congestion control behavior of the real-time
   interactive applications.

4.  IANA Considerations

   This document has no IANA actions.

5.  Security Considerations

   The security considerations in [RFC8868] and the relevant congestion
   control algorithms apply.  The principles for congestion control are
   described in [RFC2914], and in particular, any new method must
   implement safeguards to avoid congestion collapse of the Internet.

   Given the difficulty of deterministic wireless testing, it is
   recommended and expected that the tests described in this document
   would be done via simulations.  However, in the case where these test
   cases are carried out in a testbed setting, the evaluation should
   take place in a controlled lab environment.  In the testbed, the
   applications, simulators, and network nodes ought to be well-behaved
   and should not impact the desired results.  It is important to take
   appropriate caution to avoid leaking nonresponsive traffic with
   unproven congestion avoidance behavior onto the open Internet.

6.  References

6.1.  Normative References

   [HO-deploy-3GPP]
              3GPP, "Physical layer aspects for evolved Universal
              Terrestrial Radio Access (UTRA)", TS 25.814, October 2006,
              <http://www.3gpp.org/ftp/specs/
              archive/25_series/25.814/25814-710.zip>.

   [IEEE802.11]
              IEEE, "Standard for Information technology--
              Telecommunications and information exchange between
              systems Local and metropolitan area networks--Specific
              requirements Part 11: Wireless LAN Medium Access Control
              (MAC) and Physical Layer (PHY) Specifications",
              IEEE 802.11-2012,
              <https://ieeexplore.ieee.org/document/7786995>.

   [NS3WiFi]  "ns3::YansWifiChannel Class Reference",
              <https://www.nsnam.org/doxygen/
              classns3_1_1_yans_wifi_channel.html>.

   [RFC5681]  Allman, M., Paxson, V., and E. Blanton, "TCP Congestion
              Control", RFC 5681, DOI 10.17487/RFC5681, September 2009,
              <https://www.rfc-editor.org/info/rfc5681>.

   [RFC8867]  Sarker, Z., Singh, V., Zhu, X., and M. Ramalho, "Test
              Cases for Evaluating Congestion Control for Interactive
              Real-Time Media", RFC 8867, DOI 10.17487/RFC8867, January
              2021, <https://www.rfc-editor.org/info/rfc8867>.

   [RFC8868]  Singh, V., Ott, J., and S. Holmer, "Evaluating Congestion
              Control for Interactive Real-Time Media", RFC 8868,
              DOI 10.17487/RFC8868, January 2021,
              <https://www.rfc-editor.org/info/rfc8868>.

6.2.  Informative References

   [Heusse2003]
              Heusse, M., Rousseau, F., Berger-Sabbatel, G., and A.
              Duda, "Performance anomaly of 802.11b", IEEE INFOCOM 2003,
              Twenty-second Annual Joint Conference of the IEEE Computer
              and Communications Societies,
              DOI 10.1109/INFCOM.2003.1208921, March 2003,
              <https://ieeexplore.ieee.org/document/1208921>.

   [HO-def-3GPP]
              3GPP, "Vocabulary for 3GPP Specifications", 3GPP
              TS 21.905, December 2009, <http://www.3gpp.org/ftp/specs/
              archive/21_series/21.905/21905-940.zip>.

   [HO-LTE-3GPP]
              3GPP, "Evolved Universal Terrestrial Radio Access
              (E-UTRA); Radio Resource Control (RRC); Protocol
              specification", 3GPP TS 36.331, December 2011,
              <http://www.3gpp.org/ftp/specs/
              archive/36_series/36.331/36331-990.zip>.

   [HO-UMTS-3GPP]
              3GPP, "Radio Resource Control (RRC); Protocol
              specification", 3GPP TS 25.331, December 2011,
              <http://www.3gpp.org/ftp/specs/
              archive/25_series/25.331/25331-990.zip>.

   [NS-2]     "ns-2", December 2014,
              <http://nsnam.sourceforge.net/wiki/index.php/Main_Page>.

   [NS-3]     "ns-3 Network Simulator", <https://www.nsnam.org/>.

   [QoS-3GPP] 3GPP, "Policy and charging control architecture", 3GPP
              TS 23.203, June 2011, <http://www.3gpp.org/ftp/specs/
              archive/23_series/23.203/23203-990.zip>.

   [RFC2914]  Floyd, S., "Congestion Control Principles", BCP 41,
              RFC 2914, DOI 10.17487/RFC2914, September 2000,
              <https://www.rfc-editor.org/info/rfc2914>.

Contributors

   The following individuals contributed to the design, implementation,
   and verification of the proposed test cases during earlier stages of
   this work.  They have helped to validate and substantially improve
   this specification.

   Ingemar Johansson <ingemar.s.johansson@ericsson.com> of Ericsson AB
   contributed to the description and validation of cellular test cases
   during the earlier stage of this document.

   Wei-Tian Tan <dtan2@cisco.com> of Cisco Systems designed and set up a
   Wi-Fi testbed for evaluating parallel video conferencing streams,
   based upon which proposed Wi-Fi test cases are described.  He also
   recommended additional test cases to consider, such as the impact of
   EDCA/WMM usage.

   Michael A. Ramalho <mar42@cornell.edu> of AcousticComms Consulting
   (previously at Cisco Systems) applied lessons from Cisco's internal
   experimentation to the draft versions of the document.  He also
   worked on validating the proposed test cases in a virtual-machine-
   based lab setting.

Acknowledgments

   The authors would like to thank Tomas Frankkila, Magnus Westerlund,
   Kristofer Sandlund, Sergio Mena de la Cruz, and Mirja Kühlewind for
   their valuable inputs and review comments regarding this document.

Authors' Addresses

   Zaheduzzaman Sarker
   Ericsson AB
   Torshamnsgatan 23
   SE-164 83 Stockholm
   Sweden

   Phone: +46 10 717 37 43
   Email: zaheduzzaman.sarker@ericsson.com


   Xiaoqing Zhu
   Cisco Systems
   Building 4
   12515 Research Blvd
   Austin, TX 78759
   United States of America

   Email: xiaoqzhu@cisco.com


   Jiantao Fu
   Cisco Systems
   771 Alder Drive
   Milpitas, CA 95035
   United States of America

   Email: jianfu@cisco.com