Archive for July, 2013

Traditional AQM is not enough!

July 10, 2013

Note: Updated October 24, 2013, to fix some editorial nits, and to clarify the intended point that it is the combination of a working mark/drop algorithm with flow scheduling that is the “killer” innovation, rather than the specifics of today’s fq_codel algorithm.

Latency (called “lag” by gamers), once incurred, cannot be undone, as best first explained by Stuart Cheshire in his rant: “It’s the latency, Stupid.” and more formally in “Latency and the Quest for Interactivity,” and noted recently by Stuart’s 12 year old daughter, who sent Stuart a link to one of the myriad “Lag Kills” tee shirts, coffee bugs, and other items popular among gamers.lag_kills_skeleton_dark_tshirt

Out of the mouth of babes…

Any unnecessary latency is too much latency.

Many networking engineers and researchers express the opinion that 100 milliseconds latency is “good enough”. If the Internet’s worst latency (under load) was 100ms, indeed, we’d be much better off than we are today (and would have space warp technology as well!). But the speed of light and human factors research easily demonstrate this opinion is badly flawed.

Many have understood bufferbloat to be a problem that primarily occurs when a saturating “elephant flowis present on a link; testing for bufferbloat using elephants is very easy, and even a single elephant TCP flow from any modern operating system may fill any size uncontrolled buffer given time, but this is not the only problem we face. The dominant application, the World Wide Web, is anti-social to any other application on the Internet, and its collateral damage is severe.

Solving the latency problem requires a two prong attack.

(more…)

Best Practices for Benchmarking CoDel and FQ CoDel (and almost anything else!)

July 2, 2013

The bufferbloat project has had trouble getting consistent repeatable results from Some puzzle pieces of a picture puzzle.other experimenters, due to a variety of factors. This Wiki page at bufferbloat.net attempts to identify the most common omissions and mistakes. There be land mines here. Your data will be garbage if you don’t avoid them!

Note that most of these are traps for people doing network research in general, not just bufferbloat research.


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