Static vs Dynamic Domains in Network Audio: Why Buffers, Switches, and Timing Still Matter

Tinkering
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I’ve been thinking about how network audio behaves across different parts of the chain, and I wanted to share a conceptual model that has helped me understand the roles of buffers, switches, and timing.

This isn’t meant to be definitive—just a framework that might be useful for discussion.

Here’s the full model.

Static vs Dynamic Domains in Network Audio:

Why Buffers, Switches, and Timing Still Matter

This note outlines a conceptual way to think about how digital audio behaves as it moves across a network. Rather than focusing on implementation‑specific details, the goal is to provide a structural model that helps explain why certain parts of the chain influence timing, stability, and ultimately sound quality.

1. Static Domain and Dynamic Domain

Digital audio exists in two fundamentally different states, each with its own characteristics.

Static Domain

  • Data resides in memory, cache, or buffers

  • No time axis is involved

  • Jitter does not exist here

  • Only bit‑level correctness matters

Dynamic Domain

  • Data is being clocked, transferred, or converted

  • Timing uncertainty (jitter) appears as an energy‑related phenomenon

  • Power stability and load behavior influence timing precision

Understanding this distinction helps clarify why some components affect sound quality while others do not.

2. Nodes as Reset Points

Every network node—servers, switches, endpoints—acts as a temporary static domain.

Once data enters a buffer:

  • Any timing uncertainty accumulated earlier is eliminated

  • Jitter does not propagate across nodes

  • Timing is regenerated at each dynamic segment

This explains why upstream behavior still matters:
it shapes the conditions under which the next dynamic process operates.

3. The Transport Chain

TCP/IP → RAAT → Diretta → L2 Switch → DAC

(1) TCP/IP — Static Integrity

Ensures:

  • Bit‑perfect correctness

  • Packet ordering

  • Retransmission

  • Buffering

This layer preserves the purity of the static data.

(2) RAAT — Structured Static Stream

RAAT organizes static data into a stable audio stream:

  • Still largely static‑domain behavior

  • Buffering at each node resets timing

  • Prepares data for time‑domain unfolding

(3) Diretta — Reducing Dynamic Variability

Diretta operates in the dynamic domain and aims to reduce:

  • Load fluctuation

  • Power‑related disturbances

  • Transfer timing variation

It minimizes jitter generated during motion.

(4) L2 Switch — Final Dynamic Relay

The switch is the last place where packets are buffered, queued, and clocked before reaching the endpoint.

Its internal conditions—power stability, load uniformity, port behavior—shape the final timing profile delivered to the DAC.

Thus, the switch becomes the final dynamic‑domain relay.

(5) DAC — Converting Timing into Sound

The DAC converts dynamic timing into analog voltage.

Therefore:

  • Static‑domain purity (TCP/IP → RAAT)

  • Dynamic‑domain stability (Diretta → L2)

both influence the final audible result.

4. Empirical Observations

Across measurements and listening tests, several tendencies appear consistently:

  • Load stability improves downstream timing

  • Uniform network behavior reduces disturbances

  • Static load conditions help dynamic processes operate more cleanly

  • Separating noisy power domains reduces coupling

  • Diretta reduces timing variability at the endpoint

  • Cleaner upstream nodes allow the switch to operate more predictably

These observations align with the structural model above.

5. Integrated Perspective

The conceptual model and empirical tendencies reinforce each other:

  • Static‑domain purity sets the stage for dynamic precision

  • Dynamic jitter is shaped by power and load behavior

  • The switch forms the final timing profile

  • The DAC converts that timing into sound

Together, they form a coherent way to understand network‑based audio behavior.

Closing

This is simply one possible framework.
I expect that different interpretations and perspectives will reveal aspects I have not considered.
I’ll leave the discussion to everyone here.

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As a basic conceptual structure, there are a number of contradictions and inaccuracies.

Since you are new here, I will assume you are simply expressing ideas and are seeking to understand how data transmission actually works.

In order to encourage constructive and considered discussion, I am placing the thread into slow mode.

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Thanks for taking the time to comment.

My intention here is not to describe implementation‑level behavior, but to propose a conceptual framework for thinking about how different parts of the chain functionally relate to each other.

When you mention “contradictions and inaccuracies”, I’d be very interested to understand which specific points you feel are inconsistent with actual transport behavior.

If there are areas where the model can be refined or corrected, I’d genuinely appreciate the clarification.

My goal is simply to create a structure that helps explain why upstream conditions sometimes appear to influence downstream timing behavior, even when the data itself is static.

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There is so much to unpick here, that it would be futile to do so until there is consensus on what “upstream conditions” means.

For instance, for a DAC connected to a network streamer via USB, nothing upstream is relevant. Likewise, adding S/PDIF or a PC before the DAC should not change this.

It seems that you are attempting to explain things in a pseudo-technical way when the focus should be on why you believe data transmission can influence what you perceive. If done right, networks and streamers do not affect the final conversion, and the perceived differences are likely bias or psychoacoustic.

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I’ll just second this response, though add in a bit of caution:

At the moment, there is no evidence that data timing behavior, data cadence, or other conceptual variants on the theme impact audio reproduction by well-engineered and tested USB-connected DACs. RAAT and Diretta appear indistinguishable, which is what we expect from this connectivity model.

And now the caution: it remains possible that there are certain DACs and other connection patterns that may be subject to noise or other timing effects related to your suggestions, above. I have been advocating for Diretta to pursue some testing and create a playbook that shows under what circumstances the technology actually influences sound reproduction, if any.

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Is this AI nonsense by any chance?

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Certainly, the text has used AI to refine the text. The author is from Japan, so I am relaxed about its use when English isn’t the first language.

However, I am concerned by references to Diretta and the L2 switch, and therefore, the impossible transport chain.

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More Diretta advertising?

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Makes sense, although one can just use translation tools, without additional slop.

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@Londres_H, similar to the comment @mjw shared above, it looks like the Static vs Dynamic Domain framework is an attempt to reconcile bit-perfect digital transmission with the experience of hearing differences in music due to network protocols and hardware.

…the goal is to provide a structural model that helps explain why certain parts of the chain influence timing, stability, and ultimately sound quality.

What stands out is using a metaphor of “energy-related” timing vs established principles of digital signal processing. With analog tape and vinyl, where speed is energy, that metaphor works. But in the digital realm of data packets, it doesn’t hold up.

A modern digital audio system is not a continuous stream of energy, but a series of discrete, mathematically isolated layers where the timing of data delivery is irrelevant to the timing of signal reconstruction.

An alternate way of framing this is to decouple the timing of the transport layer and the timing of the audio layer - mathematically and physically separate how they operate and are described. A review of the the OSI model and TCP/IP model can help refine your approach. The rest of my comments focus on TCP/IP.

Reset Points vs TCP/IP

With network audio, the transport layer is asynchronous. Data is pulled or pushed into a buffer based on availability, not a real-time clock. Once data enters the buffer, it’s a set of bits in memory. The timing of how those bits arrived isn’t stored and can’t be passed on to the next stage. As long as the data arrives before the buffer empties, the cadence of its arrival has no impact on the cadence of its exit. The exit timing is governed solely by the local clock at the DAC.

Jitter vs Electrical Noise

You seem to be conflating the use of jitter. Let me clarify terms:

  • Network jitter is the variation in the arrival time of data packets across a network connection.
  • Digital audio jitter is timing errors in the clock signal that governs the sampling and reconstruction of digital audio signals.

I think you’re describing network jitter’s influence on perceived sound quality. If so, in a buffered system, jitter can’t spread from the network to the DAC chip.

  • Network operates in logical time (counters/timestamps)
    • Success is binary - either the bits arrive in the correct order before the buffer empties, or they do not
    • There is no quality of delivery, only completion of delivery
  • DAC operates in linear time
    • Local high-precision clock determines when each sample is converted to a voltage

Because the DAC uses its own local clock to pull data from the buffer, it is mathematically isolated from any jitter or timing energy occurring on the network.

Noise (amplitude) is EMI/RFI or leaking current that travels along the cable (ethernet/USB) and enters the DAC’s analog stage. This can raise the noise floor or cause intermodulation distortion, which may be audible.

High-quality hardware solves this through galvanic isolation using transformers or isolators, not through special network hardware.

Clock in Charge

The DAC’s internal clock is the sole arbiter of timing. The network’s job is to ensure the buffer never reaches zero (buffer under run/flow). Any perceived change in sound from network hardware is either psychoacoustic bias or analog interference from electrical noise, which should be addressed at the DAC’s input stage rather than by optimizing the network.

The endpoint device tells Roon when it needs more data. I’ll wrap up here with a pointer to RAAT’s design goals https://help.roonlabs.com/portal/en/kb/articles/raat#Design_Goals. It’s a good read.

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This seems like a very big inconsistency to me:

First you state that once data is stored in a buffer, nothing matters that happened previously. Then you use this to „explain“ why upstream behavior is supposed to matter.

There is nothing at all that leads from the former to the latter.

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Thank you both for your thoughtful comments.
To make sure we’re not talking past each other, I’d like to clarify the scope of my original post.

My intention here is not to discuss the behavior of USB DACs, where packet‑based transfer and local clocking generally isolate the DAC from upstream timing.
I fully agree with that general understanding.

However, the conceptual model I’m proposing concerns a different domain:

LAN‑based playback paths (network → streamer → DAC)

In this domain, several mechanisms operate before the audio ever reaches the DAC:

  • the streamer’s internal processing load

  • buffer refill timing and behavior

  • network‑layer timing and packet scheduling

  • switch behavior under varying traffic conditions

  • and protocols such as Diretta, which explicitly manipulate timing at the network layer

It’s also worth noting that in many practical setups,
a Diretta target often connects to the DAC via USB.
Even in those cases, the key point of this discussion is not the USB link itself,
but the network‑domain behavior upstream of the target —
where timing, buffering, and processing load can differ significantly depending on network conditions and protocol design.

So the question here is not:

“Does USB timing affect a DAC?”

but rather:

“How do network‑domain dynamics influence the streamer before the final handoff to the DAC?”

This is why I framed the discussion around static vs dynamic domains, and why timing, buffering, and switch behavior remain relevant even in modern network audio systems.

I appreciate the points raised about USB DACs, but the focus here is specifically on LAN DAC / network streamer architectures, where the interaction between network timing and internal processing can be quite different.

I’m very interested in continuing this discussion, especially regarding how different implementations (RAAT, Diretta, proprietary streamers, etc.) handle these upstream dynamics.

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If they do, the streamer is broken. End of story.

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This the crux of the issue. There is no audio before the DAC; it’s simply data traversing the network. Moreover, Diretta is demonstrably a pointless exercise that has no basis in engineering. The idea that drip feeding data rather operating devices as designed does not stand up to scrutiny.

There are neither static nor dynamic domains or network audio. It’s simply data, and the DAC almost always controls the timing, even when using interfaces such as S/PDIF.

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How do network‑domain dynamics influence the streamer before the final handoff to the DAC?

They don’t (as it relates to sound quality).

…timing, buffering, and processing load can differ significantly depending on network conditions and protocol design.

Network Domain Influence on Sound Quality
Timing Irrelevant as you’ve stated “local clocking generally isolate the DAC from upstream timing”
Buffering Irrelevant for the same reason
Processing load Relevant only if the device is corrupting the data
Network conditions Irrelevant as data packets are sent/received or they are not
Protocol Relevant only only if the protocol is changing the data

Replace my references to DAC with endpoint device, where that may be a digital transport (raspbery pi, laptop, WiiM/Lumin/Cambridge/Other), active speakers, or external DAC. With that change, there is still only completion of delivery in the network-domain.

You’ve made a claim that’s difficult to defend. Wrapping it in a static vs dynamic domain famework is not going to help. Further productive discussion should focus on specifics of how things work and not abstract models.

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At this stage, I am intentionally not joining the detailed technical debate.
My goal here is simply to clarify the intent behind the model I proposed.

Before moving toward any measurements — including listening tests —
I believe the most important step is to establish a shared conceptual framework.

In many network‑audio discussions, people jump directly to:

  • measurements

  • subjective impressions

  • protocol details

  • device‑specific behavior

But without a common set of concepts,
everyone ends up talking past each other.

The Static vs Dynamic Domains model is not meant as a final answer.
It is meant as a first draft, a starting point,
a shared language that many people can refine together.

A common conceptual base allows us to:

  • identify what should actually be measured

  • understand why certain variables matter

  • design meaningful listening tests

  • avoid category errors (USB vs LAN, buffer vs timing, etc.)

  • compare implementations on equal terms

In other words,
the purpose is not to argue for a conclusion,
but to collaboratively build the conceptual structure
that will eventually make accurate evaluation possible.

If this thread helps move toward that shared understanding,
then the model has already served its intended role as a “framework draft”.

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I disagree with your suggestion that “everyone ends up talking past each other.” Where we have measurements they eliminate the possibility that network “buffers, switches, and timing still matter.” The answer is very clear thus far: unless the DAC or streamer is poorly engineered, or the network is suffering from data delivery issues (drop outs), or there is noise transference into the DAC that is significant (i.e., that has measurable, audio impact), the concepts that you cite in the thread title do not matter, and they do not matter conceptually, as noted by others above.

Those are the facts.

So I recommend that you first justify your “thread thesis” using empirical investigation and then circle back to identifying the causal factors. Your conceptual structure has been carefully analyzed above and found to be wanting.

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But for the latter we already have both subjective and objective evaluations that quite convincingly show that Diretta does not do anything in any controlled experiment.

For the former it does not seem possible to establish a common framework by simply stringing together words that either contradict each other or just do not mean anything.

The only shared reality that we do have is the physical phenomena. If we can’t even detect any physical difference in the sound in the first place, any “framework” becomes a sophistry exercise akin to counting the number of angels that can fit on a pin head at best, and promotion of charlatans at worst.

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@Londres_H you’re new to the Roon community and we’ve pooh-poohed your first post. I imagine that’s not the desired outcome you had in mind when sharing these ideas. Assuming you’re not a shill for Diretta and can offer more than presuppositions, I commend your desire to clearly communicate with those who love music and the gear that helps them enjoy it.

If you’re serious about developing a framework and mental model in this area, I offer a couple resources for you to consider. I don’t endorse the authors’ work, but do find their ideas helpful when encountering differences in opinion about music.

  1. Moving from musical listening experience to attunement with musical events
    • “Music listening experience” served its purpose. It oriented my thinking towards the subjective reality of listening rather than the pseudo-objectivity of measurements and specifications. But it’s done its work. The clearer framework is this: home audio systems exist to render musical events in ways that support attunement. That’s the goal. Everything else follows.
  2. Overall Listening Experience (OLE) — a new Approach to Subjective Evaluation of Audio
    • Quality of Service (QoS) is from a system’s point of view, whereas Quality of Experience (QoE) is from a user or person’s point of view.
    • The evaluation of QoS requires technology-oriented methods and empirical or simulated measurements. Methods related to QoE must follow a multi-disciplinary and multi-methodological approach.
    • OLE is a subjective evaluation method that explicitly allows assessors to take every aspect into account that seems important to them when evaluating audio systems.

Lastly, I Almost Made a $15,000 Audiophile Mistake That Everyone Makes

  • YouTuber, Jay Iyagi tells a story about a highly resolving and transparent preamp that was wrong for him because memories of listening to a beloved album came from playing it on an technically inferior tube preamp.
  • What is objectively better may not always be what you like and knowing why can save you money and frustration
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Thank you for the continued discussion.
To avoid misunderstanding, let me say first that I am not making any causal claim about sound quality, nor suggesting that any protocol produces audible differences.
My goal here is simply to describe system behavior in a way that helps us talk about a complex chain without mixing different kinds of concepts.

In complex systems, different domains are often self‑contained.
Perception (sound quality), measurement, and system behavior each operate within their own context, and confusion usually comes from treating them as if they were the same domain.

In this view:

When data moves across a network, the system must do work to transmit and synchronize it.
This is the Dynamic Domain, where timing is reconstructed and electrical energy is actively injected.

When audio is prepared for playback, the system again enters the Dynamic Domain for real‑time timing work.

When data sits in a buffer or cache, no timing work is required.
This is the Static Domain, where the system is comparatively stable and the bits are simply stored.

In networking, the “connection” between domains takes the form of a protocol.
Different protocols perform the dynamic work in different ways, and those differences influence how the timing axis is rebuilt before the data returns to the Static Domain—even though the bits themselves are identical once they arrive there.

This framework is not a conclusion.
It is only an attempt to define a shared vocabulary so that we can discuss where dynamic behavior happens and where it does not, without crossing domains or talking past each other.

If any part of this framework is incomplete or inaccurate, I welcome refinement or alternative interpretations.
This is just a first attempt at a clearer map of the system.