Evaluation Test Cases for
Interactive Real-Time Media over Wireless NetworksEricsson ABLaboratoriegränd 11Luleå97753Sweden+46 107173743zaheduzzaman.sarker@ericsson.comCisco Systems12515 Research Blvd., Building 4AustinTX78759USAxiaoqzhu@cisco.comCisco Systems771 Alder DriveMilpitasCA95035USAjianfu@cisco.comCisco Systems510 McCarthy BlvdMilpitasCA95035USAdtan2@cisco.comAcousticComms Consulting6310 Watercrest Way Unit 203Lakewood RanchFL34202-5211USA+1 732 832 9723mar42@cornell.edu
TSV
Cellular NetworkWi-Fi NetworkCongestion ControlRTPThe 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.Wireless networks (both cellular and Wi-Fi )
are an integral and increasingly more significant part of the Internet. Typical
application scenarios for interactive multimedia communication over wireless include
from 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
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.The draft provides the guideline
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.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 amount 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 there will remain some
packet losses and delay variations. 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 for the definition of "handover").Handover between cells or change of serving cells (as described in
and )
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, 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 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.
The future real-time interactive application 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 capacityMobilityHandoverHowever, 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 case 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 draft
has kept as 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 exist 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 is used
for the test cases defined in this document, for example -- the LTE simulator
in . 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 Equipments (UEs) 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 are having empty buffers, 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). The investigated
congestion control algorithms should show 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 level.
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 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 to 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.
The values enclosed within "[ ]" for the following simulation attributes
follow the same notion as in .
The desired simulation setup is as follows -- Radio environment:
Deployment and propagation model: 3GPP case 1
(see )Antenna: Multiple-Input and Multiple-Output (MIMO), 2D or 3D antenna pattern.Mobility: [3km/h, 30km/h]Transmission bandwidth: 10MHzNumber of cells: multi-cell deployment
(3 Cells per Base Station (BS) * 7 BS) = 21 cellsCell radius: 166.666 MetersScheduler: Proportional fair with no priorityBearer: Default bearer for all traffic.Active Queue Management (AQM) settings: AQM [on,off]End-to-end Round Trip Time (RTT): [40ms, 150ms]User arrival model: Poisson arrival modelUser 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: 91sEvaluation period: 30s-60sMedia traffic:
Media type: VideoMedia direction: [Uplink, Downlink]Number of Media source per user: One (1)Media duration per user: 30sMedia source: same as defined in Section 4.3 of
Media Type: Audio
Media direction: Uplink and DownlinkNumber of Media source per user: One (1)Media duration per user: 30sMedia codec: Constant Bit Rate (CBR)Media bitrate: 20 KbpsAdaptation: offOther traffic models:
Downlink simulation: Maximum of 4Mbps/cell (web browsing
or FTP traffic following default TCP congestion control
)Unlink simulation: Maximum of 2Mbps/cell (web browsing
or FTP traffic following default TCP congestion control
)The goal of this test is to evaluate the performance of 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 amount of time to warm-up the network. This is to
avoid running the evaluation in an empty network where network nodes are
having empty buffers, 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).
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.Same as defined in The desired simulation setup is the same as the Varying Network Load
test case defined in except the following
changes:
Radio environment: Same as defined in
except the following:
Deployment and propagation model: 3GPP case 3
(see )Cell radius: 577.3333 MetersMobility: 3km/hUser 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 Other traffic models:
Downlink simulation: Maximum of 2Mbps/cell (web browsing
or FTP traffic following default TCP congestion control
)Unlink simulation: Maximum of 1Mbps/cell (web browsing
or FTP traffic following default TCP congestion control
)The evaluation criteria document
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 utilizations.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.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 , 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 impact 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. 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 ) should
be collected for each test case. We recommend to carry out the test cases as defined in this document using a simulator,
such as or . 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.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
as in , it is still worthwhile to
run through these tests as sanity checks. shows the network topology
of Wi-Fi test cases. The test contains multiple mobile nodes (MNs) connected
to a common Wi-Fi access point (AP) and their corresponding wired clients on
fixed nodes (FNs). Each connection carries either a 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
bi-directional. The total number of uplink/downlink/bi-directional flows for
RTP-based media traffic and TCP traffic are denoted as N and M, respectively.Test duration: 120sWi-Fi network characteristics:
Radio propagation model: Log-distance path loss propagation
model (see )PHY- and MAC-layer configuration: IEEE 802.11nMCS Index at 11: 16-QAM 1/2, Raw Data Rate at 52MbpsWired path characteristics:
Path capacity: 1MbpsOne-Way propagation delay: 50ms.Maximum end-to-end jitter: 30msBottleneck queue type: Drop tail.Bottleneck queue size: 300ms.Path loss ratio: 0%.Application characteristics:
Media Traffic:
Media type: VideoMedia direction: See Number of media sources (N): See Media timeline:
Start time: 0s.End time: 119s.Competing traffic:
Type of sources: long-lived TCP or CBR over UDPTraffic direction: See Number of sources (M): See Congestion control: Default TCP congestion control
or constant-bit-rate (CBR) traffic over UDP.Traffic timeline: See Single uplink RTP-based media flow: N=1 with uplink direction and M=0.One pair of bi-directional RTP-based media flows: N=2 (i.e., one uplink
flow and one downlink flow); M=0.One pair of bi-directional 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 bi-directional 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-live 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.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.Bi-directional 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-live 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.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.Same as defined in Test duration: 120sWi-Fi network characteristics:
Radio propagation model: Log-distance path loss propagation
model (see )PHY- and MAC-layer configuration: IEEE 802.11nMCS Index at 11: 16-QAM 1/2, Raw Data Rate at 52MbpsWired path characteristics:
Path capacity: 100Mbps.One-Way propagation delay: 50ms.Maximum end-to-end jitter: 30ms.Bottleneck queue type: Drop tail.Bottleneck queue size: 300ms.Path loss ratio: 0%.Application characteristics:
Media Traffic:
Media type: VideoMedia direction: See .Number of media sources (N): See .Media timeline:
Start time: 0s.End time: 119s.Competing traffic:
Type of sources: long-lived TCP or CBR over UDP.Number of sources (M): See .Traffic direction: See .Congestion control: Default TCP congestion control
or constant-bit-rate (CBR) traffic over UDP.Traffic timeline: See .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 52Mbps, the total application-layer throughput (assuming
reasonable distance, low interference and infrequent contentions caused by competing
streams) is around 20Mbps. A total of N=16 RTP-based media flows (with a maximum
rate of 1.5Mbps 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 bi-directional 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 bi-directional 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 bi-directional 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 bi-directional 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 distributes
within a window of t=0-10s; their end times are randomly distributed within a window of
t=110-120s. 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 bi-directional 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 bi-directional 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 bi-directional 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 bi-directional 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).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.As discussed in , 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., 2Mbps to 54Mbps) for investigating its effect on the
congestion control behavior of the real-time interactive applications.This memo includes no request to IANA.The security considerations in
and the relevant congestion control algorithms apply. The principles for congestion
control are described in , 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 non-responsive traffic with unproven congestion avoidance behavior onto
the open Internet.The authors would like to thank Ingemar Johansson for contributing to the cellular
test cases during the earlier stage of this draft. The authors would like to thank Tomas Frankkila, Magnus Westerlund,
Kristofer Sandlund, Sergio Mena de la Cruz, and Mirja Kuehlewind for their
valuable inputs and review comments regarding this draft.Physical layer aspects for evolved Universal Terrestrial
Radio Access (UTRA)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) SpecificationsWi-Fi Channel Model in ns-3 SimulatorVocabulary for 3GPP Specifications3GPPE-UTRA- Radio Resource Control (RRC); Protocol
specification3GPPRadio Resource Control (RRC); Protocol specification3GPPPolicy and charging control architecturens-2ns-3 Network SimulatorPerformance anomaly of 802.11b