Drew,
(in theory, and based upon number of peers, data): If you have a network with these upstream connections to the Internet you should see inbound traffic utilization in this order:
AS Name --------- 3356 Level3 7018 ATT 3549 Global Crossing 4323 Time Warner Telecom 10796 TimeWarnerCable/RR
In short (and not to repeat what others have said, but simply point out a different reason), the Internet is an example of a large anisotropic system. The implication for 'inbound traffic distribution' will not only depend in Neighbor-AS policies (upstream of your own AS, mind you), but equally (if not moreso) on the traffic matrix your users (or host systems, applications, etc) generate as a consequence of their activities. Almost entire decoupled from "pull heavy," "push heavy," or so-called "balanced" (in the bits/sec sense) traffic patterns, quite simply, "what you're doing" will influence the distribution. This will change over time, too, especially if the source of the traffic reaching you via 3356 experiences a change in a business relationship (174 and 3356 de-peer, again).
I am trying to determine why I am seeing it in this order:
3356 Level3 4323 Time Warner Telecom 3549 Global Crossing 10796 TimeWarnerCable/RR 7018 ATT
Netflow or sflow will likely shed light on "why?" with a higher degree of certainty than AS-AS adjacencies. Knowing both the rendezvous mechanism and the application inducing the flow(s) would be the first step to answering "why did that reach us via (3) and not some other edge we know exists?" Additionally, how apps discover both the network and content is a topic being explored by several researchers and operators, and may be relevant to your question. You may be able to tease out further data by considering these mechanisms as you go about monitoring. Dave Plonka is working on as much, but as of yet, I can't find a paper - only presentations [*]. Best, -Tk [*]: "Rendezvous-based Network Traffic Analysis" - http://www.cio.wisc.edu/events/lockdown/09/presentations.aspx#plonka