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Re: "Selfish Routing"
- From: Mike Lloyd
- Date: Sat Feb 15 20:20:33 2003
Iljitsch van Beijnum wrote:
Pure utilization-based routing between 2 AS's is, in effect, load
balancing, so I'm not sure how to interpret your first instance. But in
any case, adding performance objectives to a load optimization problem
makes the solution more demanding. (It is possible in practice to
observe performance differences between 2 paths from AS A to directly
connected AS B - not as many as you see comparing different transit
choices to a far point, but they still exist.)
Utilization-based routing between two ASes is an excercise in futility
if it's in a single location (load balancing is simpler and just as
effective) and isn't simpler than across multiple ASes if the
interconnects are in different places of the network topology
Optimization across topologically distant egress points from AS A to AS
B is harder, and if the choice is a nearby link to B and a far link to
some other AS C, harder still. But in practical networking, this is not
the common problem.
Practically speaking, most AS's fall between your two cases - that is,
they have at least one place in their topology where they border several
other AS's. This provides multiple pre-computed, loop-free paths to the
same end point. Picking the "best" one for near-optimal performance and
low congestion in this context is, I would suggest, beneficial, and if
done correctly, not prone to the suboptimality discussed in the paper
that started this thread.
Given good end to end performance measurement as part of the path
selection, a planet-circling route is unlikely. Few apps will perform
well if packets have to circumnavigate (streaming and email are among
the only candidates).
Besides, the whole point is that you'd be able to go from New York to
London over Tokio if the direct line is congested.
So to an extent, I agree - performing dynamic re-routing over arbitrary
paths purely to avoid congestion isn't a great idea. You can indeed end
up bouncing of satellites. But if you add performance sensitivity, you
have a harder optimization challenge, but a much more worthwhile result.