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It's useful to note that this scaling comes with the same coding models -- the same code runs which measures small IoT devices without overloading their CPUs as severs with hundreds of cores that run 50Gbps pipes.

It's a great demonstration how the Windows OS will scale naturally. We have added features over time which we found greatly helps in measuring the reliability of a networking deployment. Below are examples of combinations of options we have found to be particularly useful in discovering issues in networking components and devices.

While thankfully rare, we have found one method has been particularly successful in discovering data corruption issues in hardware and software stacks. This has found data corruption issues across a variety of vendors and deployments. Interestingly in most cases it was only ctsTraffic and only when ctsTraffic was run in this way was the data corruption observed.

The unique bit here was running the "full duplex" pattern. This data pattern will send and receive at line rate concurrently: sends posting as quickly as they can post, receives Router Round Over Bit Sizes 80 posting as quickly as they can post, all in parallel. This often results in making software work the "hardest" as it must be tracking each TCP stream of data going in both directions, at line rate.

With some 40 Gbps network devices we would only discover corruptions when running the duplex pattern at full 40 Gbps bidirectional line rate. Note that scaling the number of connections and transfer size of each connection as one goes above 1Gbps does also help as it allows more time for each connection.

If a network deployment continues to have trouble scaling to line rate, specifying the buffer sizes to 1MB can help -buffer If one wants to work even harder to find data corruption bugs, one can instruct ctsTraffic to randomize the buffer sizes used for each send and receive request.

This will often change the buffering patterns across a networking stack, as TCP segments get created of different sizes which can influence many other TCP factors, such as packet sizes and window sizes.

The default value is 64k for all IO requests on all connections. Randomizing buffer sizes can be done by specifying a range with square brackets. The below is an example where each TCP connection would be randomly choosing a buffer size to use for that connection between 1KB and 1MB.

As noted previously, adjusting numbers of connections and the total transfer size can be useful especially when working on deployments beyond 1Gbps. If one wants to work even harder to find issue in connection establishment, there are options which can be used to force many more connections to happen over time. The combination tells ctsTraffic a maintain a lot of concurrent connections, and b each connection should be very short-lived.

In the output from the run we can see in the Completed column that we were Round Over Router Bit Sizes Llc quickly iterating through many thousands of successful connections. One should also note that at around the 55 second mark we started seeing errors. Because the default behavior for ctsTraffic is for the clients to issue a graceful shutdown at the end of a connection, we create a 4-way FIN to gracefully tear down that TCP connection.

While this is a typical way clients and servers terminate connections this can result in the client's tuple its IP and port to be temporarily held in a "time-wait" state per RFC. While in these states that port cannot be reused. We have options in ctsTraffic which can help to work around this issue: one can tell ctsTraffic how to terminate each successful connection. To avoid entering time-wait, we can tell ctsTraffic to force a RST to shutdown the connection.

The command line with this combination would like this:. The -shutdown option either 'graceful' or 'rude' will instruct the client in how to end their connection the server will always wait for the client to initiate a closure and therefore never enter time-wait -- something we highly recommend to those building server software.

As you see in our simple example instead of seeing failures after about 16, connections, we were still creating successful connections after 20, connections. In our UDP stream implementation, every datagram is tagged by number and by time. Thus, the client receiving the stream of datagrams from the server can accurately identify every dropped datagram as well as validating the data integrity of each received datagram the same bit-pattern analysis occurs with UDP as with TCP to check for data corruption.

It's recommended to start with current stream behaviors -- to replicate and measure those streams over time. To express this in scenario terms, Netflix of often streaming much of its p 4K content at We can accurately measure a deployment's ability to stream a 4K movie at these rates.

We will accurately send the specified stream and upon receiving verify the data integrity of all datagrams, track all lost frames which would translate to lost packets , and track all repeated frames which can happen with various network topologies. These options specify for the client to send a datagram to the server to initiate a "connection" -- where the server will be sending 25Mbps of data across 60 "frames" datagrams per second.

Buffer depth is how much of a time allowance the client will allow for variance in receiving datagrams. The result of this test produces 3 log files, 2 similar to the TCP logs and one which tracks jitter by comparing time stamps within the received datagrams.

Note that the -consoleverbosity: flag controls the type and detail of what it output to the console like with TCP, setting 0 turns off all output.

The banner under Configured Settings shows default settings with how the streaming parameters were turned into datagram rates. In the same sample as above, three log files were created due to the following command line options: " -statusfilename:udpclient. The status file writes out the same information to a csv as is written to console with the above " -consoleverbosity:1 " option set.

This is similar to the TCP connection view, this time with aggregate data points for each connection. Below is the connection output:. When making a test run with just a single UDP connection , the client can also track jitter information. This is collected by tracking every individual datagram received and looking at the times stamped on it by the server.

Even though the client and server are not time synchronized, the client can still analyze the latency deltas by using the first datagram received as its baseline and calculating gaps. Because the client and server had the same parameters specified, the client know the number of milliseconds that the server would have been waiting between calls to send.

By subtracting the known timer value when the server was waiting between sends it can calculate the time between the actual send and the resulting receive. As a trivial example, here is jitter being tracked over loopback for the first 30 datagrams received:. The chart shows the sender and receiver QueryPerformanceCounter and QueryPerformanceFrequency values which ctsTraffic stamped in the datagram payload.

You'll note that being over loopback and given optimizations the math resulted in the time in flight being negative. As a more interesting example, running the above 25Mbps stream from a small Surface laptop over Wi-Fi to another machine also connected over Wi-Fi shows more diverse data. The status output now shows more variance in throughput as well as infrequent packet drops.

Just as useful we can look at Jitter data in a more relevant scenario -- here are the first 20 frames:. We can see that variance drifted quite a bit, with larger gaps with a few negative gaps as datagrams arrived in bursts. Graphing this information gives us insightful views into the variance between datagrams received:.

With these views we can now see the variance distribution over this 60 second 25 Mbps stream of datagrams. Skip to content. Branches Tags. Nothing to show. Go back.

Launching Xcode If nothing happens, download Xcode and try again. Additionally, you may change the audio format and quality that a remote user is sending to you. The compressed formats available introduce a small amount of additional latency 2.

Additionally if you use the PCM uncompressed options the network packet sending will take advantage of the possible smaller audio sample buffer sizes you may have configured in the audio setup to reduce latency. The compressed audio formats have a minimum sample frame size of samples, while the PCM formats do not have a lower limit.

You can certainly still use audio sample buffer sizes less than even when using the compressed send quality, however it will only improve your own monitoring latency, and not the end-to-end network latency.

Sometimes you may try to connect with a group and one or more of the people in it may show up with an error message indicating that one of you may be behind an incompatible router and need to set up port forwarding in your internet router. The first thing to try in this case is actually to just Disconnect from the group and re-connect, sometimes this will resolve the issue.

Other times it is a true incompatibility because one of the people may be on an institutional network corporate or educational and they often are configured to be unfriendly to peer-to-peer networking. One thing you can do that often helps, if you have access to the administration dashboard of your own home internet router, is to set up port forwarding.

Often this is enough to help resolve issues like this. To use port forwarding, the computer running SonoBus must have a fixed internal IP address on your home network. You will need to manually set the IP address on your computer to one in the X or other range used by your router as well as to make sure that address you select is outside the range of those that the router will use for assigning IP addresses to other devices dynamically.

There are many articles on the Internet for setting up a fixed IP address for a computer on your local network, that procedure is beyond the scope of this guide. This address should be the fixed address you set your computer to use as described above. If you want to see the people you are playing with, you can run Zoom in parallel along with SonoBus.

Simply start a new Zoom meeting and invite your SonoBus session players to join it via sending them the Zoom meeting link via email or other messaging system. Ask them to join the Zoom meeting either without audio, or to mute their audio in the meeting. The video will be somewhat out-of-sync with the SonoBus audio, but it is still very nice to be able to see the other players.

In our initial tests, we found that there was about a ms sync difference, with the Zoom video the lagging SonoBus audio.

Running Zoom appeared to have no negative effect on SonoBus performance or latency. In our case, we launched Zoom after our SonoBus session was already established.

SonoBus Website sonobus. SonoBus Google Group groups. SonoBus YouTube Channel www. The following linked spreadsheet was originally put together by Kevin Kriner for users of JamKazam.

It is well supported on essentially every computer and mobile platform, and the technological barrier to entry is very low. Most users are able to get up and running on Zoom quickly and are able to participate at some level in online sessions. The technological barriers for using SonoBus are a bit higher than for Zoom particularly if the player is looking to optimize their setup to have the lowest possible latency playing with others.

A user ideally has to understand about WDM vs. Ethernet connections, network jitter, etc. If they are comfortable with diving into the settings on their system, or if they already have experience with using DAW software like Pro Tools or Reaper, particularly if they already have experience configuring a low-latency USB or PCIe audio interface, then I actively encourage them to give it a try.

Even if they are currently connected via WiFi, testing on WiFi does allow for checking that their audio subsystem is functioning correctly even if they may have high network latency and jitter issues. If all is good as far as the user is able to connect via WiFi, then the next step would be to connect via a hardwire Ethernet cable.

Most desktop systems have Ethernet connectors, but many laptops will require investing in a USB-C to Ethernet adapter. If the audio latency is high because of perhaps an inefficient internal audio subsystem, then the next step would be to purchase a low-latency USB or PCIe audio interface from the list of recommended interfaces found in Appendix A of this document.

I encourage experienced users of SonoBus to have a one-on-one test session with new users to help them optimize their settings and get familiar with the platform. I am very excited about SonoBus and looking forward to playing with you live in real time in the near future on a SonoBus session!

The trick is going to the Filters section of an audio input source you can make a new one, or use an existing one you already have , press the cogwheel on the input source and select Filters. Then add a new filter, and choose SonoBus from the plugin list in there. OBS does not run at a particularly low latency, so if you also want to be a performer with a group that you also want to stream out via OBS you will want to also run a separate SonoBus maybe standalone version where you connect directly with the audio interface and can set it to use a small buffer size.

You can connect to the same group as the plugin version running in OBS as well as with other people. It can always get confusing when running multiple SonoBuses on the same machine regarding monitoring, etc. Other low-latency multi-user peer-to-peer audio systems have similar audio hardware and system configuration requirements as SonoBus.

These articles, while not specifically about SonoBus, may be useful in optimizing your system for SonoBus:. SonoBus was developed by Jesse Chappell, Sonosaurus LLC, but building on the shoulders of many other open source software libraries see source code for details. Features Tips User Guide Download. Windows 7, Windows 8 and Windows 10 are all reported to be working well with SonoBus. SonoBus should also work in Linux on a variety of hardware platforms.

An installed copy of the Mac, Windows or iOS SonoBus client Linux clients can be built from source code, but there are no installable packages for it yet. WiFi works, but is an extra layer of packet sequencing and always adds a lot of jitter, requiring increased buffer sizes.

SonoBus strongly recommends connection by Ethernet. Recommended: Wired headphones or earbuds. Bluetooth headphones will not work because of the added delay as much as ms inherent in Bluetooth audio.

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