Tony – Thanx for picking up the discussion. Thanx also for doing the math to show that bandwidth is not a concern. I think most/all of us knew that – but it is good to put that small question behind us.
I also think we all agree on the goal - which is to flood significantly faster than many implementations do today to handle deployments like the case you mention below. Beyond this point, I have a different perspective. As network-wide convergence depends upon fast propagation of LSP changes – which in turn requires consistent flooding rates on all interfaces enabled for flooding – a properly provisioned network MUST be able to sustain a consistent flooding rate or the operation of the network will suffer. We therefore need to view flow control issues as indicative of a problem. It is a mistake to equate LSP flooding with a set of independent P2P “connections” – each of which can operate at a rate independent of the other. If we can agree on this, then I believe we will have placed the flow control problem in its proper perspective – in which case it will become easier to agree on the best way to implement flow control. Les From: Lsr <lsr-boun...@ietf.org<mailto:lsr-boun...@ietf.org>> On Behalf Of Tony Li Sent: Tuesday, July 23, 2019 6:34 AM To: lsr@ietf.org<mailto:lsr@ietf.org> Subject: [Lsr] Dynamic flow control for flooding Hi all, I’d like to continue the discussion that we left off with last night. The use case that I posited was a situation where we had 1000 LSPs to flood. This is an interesting case that can happen if there was a large network that partitioned and has now healed. All LSPs from the other side of the partition are going to need to be updated. Let’s further suppose that the LSPs have an average size of 1KB. Thus, the entire transfer is around 1MB. Suppose that we’re doing this on a 400Gb/s link. If we were to transmit the whole batch of LSPs at once, it takes a whopping 20us. Not milliseconds, microseconds. 2x10^-5s. Clearly, we are not going to be rate limited by bandwidth. Note that 20us is an unreasonable lower bound: we cannot reasonably expect a node to absorb 1k PDUs back to back without loss today, in addition to all of it’s other responsibilities. At the opposite end of the spectrum, suppose we transmit one PDU every 33ms. That’s then going to take us 33 seconds to complete. Unreasonably slow. How can we then maximize our goodput? We know that the receiver has a set of buffers and a processing rate that it can support. The processing rate will vary, depending on other loads. What we would like the transmitter to do is to transmit enough to create a small processing queue on the receiver and then transmit at the receiver’s processing rate. Can we agree on this goal? Tony
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