Earlier quoted context omitted.
As a general question, I'm curious how a tactile learner might be able to get a decent grasp of pretty much everything you just described, in a practical setting, without breaking the bank. :) How good is GNSS at simulating latency, buffer saturation, etc on a simulated network and how much complexity would I need to contemplate factoring in to build an accurate model of the average organically evolved, ad-hoc, multi…
It really is a matter of learning the hard way the phenomena that show up on real networks in the wild. Aspera spent a decade incorporating responses to all these lessons into their code. You can get 80% there quickly, 90% there in two years, but the rest is just hard. A versatile simulation environment feeding the algorithm with synthetic time events according to a configured schedule is probably the best way to ram…
Hearing I can get to 80% quickly is encouraging from a MVP viability point of view, thanks. (And also from a fail-fast perspective; I've now gotten to wondering how much additional performance might be eked out of start-stop style traffic, and it's good to know it won't take long to find out whether the pursuit is worthless or not. Yay.)
I read the second half of that second paragraph as describing a network model simulation that "compiles" a particular routing graph/topology into a set-in-stone sequence of packet events that you then later analyze...? (I'm interpreting "the algorithm" is my target application code, and "synthetic time events" and "configured schedule" as hints at non-real-time pregeneration. This may be incorrect.)
Eek, the delay distributions you describe almost sound like they might be NP-complete to solve.