Credit-based Shaper and Time-aware Shaper¶
The Model¶
Here is the network:
Here is the configuration:
[General]
network = inet.networks.tsn.TsnLinearNetwork
sim-time-limit = 1s
description = "Traffic shaping using mixed asynchronous and credit-based shapers"
# client applications
*.client.numApps = 2
*.client.app[*].typename = "UdpSourceApp"
*.client.app[0].display-name = "best effort"
*.client.app[1].display-name = "video"
*.client.app[*].io.destAddress = "server"
*.client.app[0].io.destPort = 1000
*.client.app[1].io.destPort = 1001
*.client.app[*].source.packetLength = 1000B - 54B # 42B = 8B (UDP) + 20B (IP) + 14B (ETH MAC) + 4B (ETH FCS) + 8B (ETH PHY)
*.client.app[0].source.productionInterval = exponential(200us) # ~40Mbps
*.client.app[1].source.productionInterval = exponential(400us) # ~20Mbps
# server applications
*.server.numApps = 2
*.server.app[*].typename = "UdpSinkApp"
*.server.app[0].display-name = "best effort"
*.server.app[1].display-name = "video"
*.server.app[0].io.localPort = 1000
*.server.app[1].io.localPort = 1001
# enable outgoing streams
*.client.hasOutgoingStreams = true
# enable incoming streams
*.server.hasIncomingStreams = true
# client stream identification
*.client.bridging.streamIdentifier.identifier.mapping = [{stream: "best effort", packetFilter: expr(udp.destPort == 1000)},
{stream: "video", packetFilter: expr(udp.destPort == 1001)}]
# client stream encoding
*.client.bridging.streamCoder.encoder.mapping = [{stream: "best effort", pcp: 0},
{stream: "video", pcp: 4}]
# switch stream decoding
*.switch.bridging.streamCoder.decoder.mapping = [{pcp: 0, stream: "best effort"},
{pcp: 4, stream: "video"}]
# enable egress traffic shaping
*.switch.hasEgressTrafficShaping = true
# credit-based and asynchronous traffic shaping
*.switch.eth[*].macLayer.queue.numTrafficClasses = 2
*.switch.eth[*].macLayer.queue.*[0].display-name = "best effort"
*.switch.eth[*].macLayer.queue.*[1].display-name = "video"
*.switch.eth[*].macLayer.queue.transmissionSelectionAlgorithm[0].typename = "Ieee8021qCreditBasedShaper"
*.switch.eth[*].macLayer.queue.transmissionSelectionAlgorithm[0].idleSlope = 60Mbps
*.switch.eth[*].macLayer.queue.transmissionSelectionAlgorithm[1].typename = "Ieee8021qCreditBasedShaper"
*.switch.eth[*].macLayer.queue.transmissionSelectionAlgorithm[1].idleSlope = 60Mbps
*.switch.eth[*].macLayer.queue.transmissionGate[0].initiallyOpen = true
*.switch.eth[*].macLayer.queue.transmissionGate[1].initiallyOpen = false
*.switch.eth[*].macLayer.queue.transmissionGate[*].durations = [4ms, 2ms]
Results¶
The following video shows the behavior in Qtenv:
Here are the simulation results:
Sources: omnetpp.ini
Try It Yourself¶
If you already have INET and OMNeT++ installed, start the IDE by typing
omnetpp, import the INET project into the IDE, then navigate to the
inet/showcases/tsn/trafficshaping/cbsandtas folder in the Project Explorer. There, you can view
and edit the showcase files, run simulations, and analyze results.
Otherwise, there is an easy way to install INET and OMNeT++ using opp_env, and run the simulation interactively.
Ensure that opp_env is installed on your system, then execute:
$ opp_env run inet-4.4 --init -w inet-workspace --install --chdir \
-c 'cd inet-4.4.*/showcases/tsn/trafficshaping/cbsandtas && inet'
This command creates an inet-workspace directory, installs the appropriate
versions of INET and OMNeT++ within it, and launches the inet command in the
showcase directory for interactive simulation.
Alternatively, for a more hands-on experience, you can first set up the workspace and then open an interactive shell:
$ opp_env install --init -w inet-workspace inet-4.4
$ cd inet-workspace
$ opp_env shell
Inside the shell, start the IDE by typing omnetpp, import the INET project,
then start exploring.