I've been playing around with resumptions lately, mostly from Abramsky's classic paper Retracing Some Paths in Process Algebra. They are quite slick (basically solutions to the domain equation $R = I \to (O \times R)$), and very reminiscent of Kahn networks.
Of course, this observation is not original to me --- they form a traced monoidal category, and this fact was used by Abramsky and Jagadeesan to give semantics to linear logic. At any rate, note that if you feed a resumption $r$ an input of type $I$, you get an output of type $O$ and an updated resumption $r'$, which is what lets you model the fact that a dataflow node can change as it sees inputs come in.
As a result, it seems like they could give a nice API for building I/O transducers in a higher-order language like ML or Haskell, but I can't seem to find any papers describing such a thing. But they've been around for decades, and Gordon Plotkin invented them, so it's not like they've languished in obscurity. So I was wondering if anyone had seen them put to such use.