Evaluation Test Cases for Interactive Real-Time Media over Wireless NetworksEricsson ABTorshamnsgatan 23Stockholm164 83Sweden+46 10 717 37 43zaheduzzaman.sarker@ericsson.comCisco SystemsBuilding 412515 Research BlvdAustinTX78759United States of Americaxiaoqzhu@cisco.comCisco Systems771 Alder DriveMilpitasCA95035United States of Americajianfu@cisco.com
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.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
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Table of Contents
. Introduction
. Cellular Network Specific Test Cases
. Varying Network Load
. Network Connection
. Simulation Setup
. Expected Behavior
. Bad Radio Coverage
. Network Connection
. Simulation Setup
. Expected Behavior
. Desired Evaluation Metrics for Cellular Test Cases
. Wi-Fi Networks Specific Test Cases
. Bottleneck in Wired Network
. Network Topology
. Test/Simulation Setup
. Typical Test Scenarios
. Expected Behavior
. Bottleneck in Wi-Fi Network
. Network Topology
. Test/Simulation Setup
. Typical Test Scenarios
. Expected Behavior
. Other Potential Test Cases
. EDCA/WMM usage
. Effect of Heterogeneous Link Rates
. IANA Considerations
. Security Considerations
. References
. Normative References
. Informative References
Contributors
Acknowledgments
Authors' Addresses
IntroductionWireless 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
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. 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.Cellular Network Specific Test CasesA 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 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, 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 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 . Varying Network LoadThe 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). Network ConnectionEach 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.
Simulation Topology
uplink
++))) +-------------------------->
++-+ ((o))
| | / \ +-------+ +------+ +---+
+--+ / \----+ +-----+ +----+ |
/ \ +-------+ +------+ +---+
UE BS EPC Internet fixed
<--------------------------+
downlink
Simulation SetupThe 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:
[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
Maximum of 4 Mbps/cell (web browsing or FTP traffic following default TCP congestion control
)
Uplink simulation:
Maximum of 2 Mbps/cell (web browsing or FTP traffic following default TCP congestion control
)
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.Bad Radio CoverageThe 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).Network ConnectionSame as defined in .Simulation SetupThe desired simulation setup is the same as the Varying Network Load
test case defined in except for the following
changes:
Maximum of 2 Mbps/cell (web browsing or FTP traffic following default TCP congestion control )
Uplink simulation:
Maximum of 1 Mbps/cell (web browsing or FTP traffic following default TCP congestion control )
Expected BehaviorThe 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.Desired Evaluation Metrics for Cellular Test CasesThe 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 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.
Wi-Fi Networks Specific Test CasesGiven 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 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 ) should
be collected for each test case. We recommend carrying 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.Bottleneck in Wired NetworkThe 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 , it is still worthwhile to
run through these tests as sanity checks.Network Topology 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.Network Topology for Wi-Fi Test Cases
Uplink
+----------------->+
+------+ +------+
| MN_1 |)))) /=====| FN_1 |
+------+ )) // +------+
. )) // .
. )) // .
. )) // .
+------+ +----+ +-----+ +------+
| MN_N | ))))))) | | | |========| FN_N |
+------+ | | | | +------+
| AP |=========| FN0 |
+----------+ | | | | +----------+
| MN_tcp_1 | )))) | | | |======| FN_tcp_1 |
+----------+ +----+ +-----+ +----------+
. )) \\ .
. )) \\ .
. )) \\ .
+----------+ )) \\ +----------+
| MN_tcp_M |))) \=====| FN_tcp_M |
+----------+ +----------+
+<-----------------+
Downlink
Test/Simulation Setup
Test duration:
120 s
Wi-Fi network characteristics:
Radio propagation model:
Log-distance path loss propagation model (see )
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
Number of media sources (N):
See
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
Number of sources (M):
See
Congestion control:
Default TCP congestion control or CBR traffic over UDP
Traffic timeline:
See
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.
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.
Bottleneck in Wi-Fi NetworkThe 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.Network TopologySame as defined in .Test/Simulation Setup
Test duration:
120 s
Wi-Fi network characteristics:
Radio propagation model:
Log-distance path loss propagation model (see )
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
Number of media sources (N):
See
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
Traffic direction:
See
Congestion control:
Default TCP congestion control or CBR traffic over UDP
Traffic timeline:
See
Typical Test ScenariosThis 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.
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).
Other Potential Test CasesEDCA/WMM usageThe 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.Effect of Heterogeneous Link RatesAs 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., 2 Mbps to 54 Mbps) for investigating its effect on the
congestion control behavior of the real-time interactive applications.IANA ConsiderationsThis document has no IANA actions.Security ConsiderationsThe 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 nonresponsive traffic with unproven congestion avoidance behavior onto
the open Internet.ReferencesNormative ReferencesPhysical layer aspects for evolved Universal Terrestrial Radio Access (UTRA)3GPPStandard 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) SpecificationsIEEEns3::YansWifiChannel Class ReferenceTCP Congestion ControlThis document defines TCP's four intertwined congestion control algorithms: slow start, congestion avoidance, fast retransmit, and fast recovery. In addition, the document specifies how TCP should begin transmission after a relatively long idle period, as well as discussing various acknowledgment generation methods. This document obsoletes RFC 2581. [STANDARDS-TRACK]Test Cases for Evaluating Congestion Control for Interactive Real-Time MediaEvaluating Congestion Control for Interactive Real-Time MediaInformative ReferencesPerformance anomaly of 802.11bIEEE INFOCOM 2003Twenty-second Annual Joint Conference of the IEEE Computer and Communications SocietiesVocabulary for 3GPP Specifications3GPPEvolved Universal Terrestrial Radio Access (E-UTRA); Radio Resource Control (RRC); Protocol specification3GPPRadio Resource Control (RRC); Protocol specification3GPPns-2ns-3 Network SimulatorPolicy and charging control architecture3GPPCongestion Control PrinciplesThe goal of this document is to explain the need for congestion control in the Internet, and to discuss what constitutes correct congestion control. This document specifies an Internet Best Current Practices for the Internet Community, and requests discussion and suggestions for improvements.ContributorsThe 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.s.johansson@ericsson.com>
of Ericsson AB contributed to the description and validation of cellular test cases
during the earlier stage of this document. <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. <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.AcknowledgmentsThe authors would like to thank
,
,
,
, and
for their
valuable inputs and review comments regarding this document.Authors' AddressesEricsson ABTorshamnsgatan 23Stockholm164 83Sweden+46 10 717 37 43zaheduzzaman.sarker@ericsson.comCisco SystemsBuilding 412515 Research BlvdAustinTX78759United States of Americaxiaoqzhu@cisco.comCisco Systems771 Alder DriveMilpitasCA95035United States of Americajianfu@cisco.com