Internet Signal Processing: Next Steps

photohomoeopathAI and Robotics

Nov 24, 2013 (3 years and 4 months ago)


Internet Signal Processing:

Next Steps

Dr. Craig Partridge

BBN Technologies

Defining Signal Processing


such as shaping, converting,
enhancing, and time positioning


(such as packet traces), to

signals into other forms

such as shapes,
power levels, or images

and thereby

features from the original signal.

Internet Signal Processing

While there have been brief uses in the past

E.g. Jacobson on timing

We’re only now seeing an emerging community
of people doing signal processing on Internet

And most of that community is in this room

Where should we, as a community, be headed?

This is not a question we’ve had a chance to consider as
a group (thus this workshop)

Whither? In Three Questions

Is there more to signal processing than
pretty pictures?

What can signal processing illuminate?

What are the limits of different algorithms?

What should our input signals be?

Pretty Pictures

Why do we create pretty pictures?

Initial experiments with an algorithm

Try it on things and see what pops out

The danger comes when we publish those pictures
without understanding them

“This traffic pattern causes this picture” is something
we should aim not to do

Unless you’re asking for help

Seek rather “This traffic pattern causes this picture

Some Not
Ready Pictures

time analysis

transmission time vs.
transmission time

Bands represent observed
acceptable transmission

Low part of chart may
reveal MAC layer in

What Can We Illuminate?

What can signal processing tell us about the

We need to find out.


Seek out algorithms and try them

Seek out problems and find algorithms that might
answer them

Seek out inputs to feed to algorithms we understand

At this point, we probably need to try all three

Some Thought Questions

How much does cross traffic “imprint”?

What are wavelets good for?

When are wavelets the wrong approach?

What role for match


Propagation of self
similarity work…

An intriguing result from signal processing…

Characteristics from all three flows observed

But only two visible to sensor!

Pros and Cons of Wavelets


we’ve used them a lot and we understand a few things

how to compute Hurst parameter

how their details tend to vary


they’re bad at identifying particular frequencies

often hard to say exactly why details vary

BTW: these are questions we should ask ourselves
about any technique going forward


A technique for extracting signals from noisy


signals to have a structure that enables the extraction

that we be sure the signals are present

One useful structure: signals expressable in max
plus algebra

TCP is max
plus (SIGCOMM 2000)

What Should Input Signals Be?

Typical practice:

take a packet trace

post process it into a signal

sample it in some fashion (method usually not
described in paper…)

usually only use arrival time and length

usually resulting in either bins of event counts or a
1,0,1) uniformly sampled signal

Why Can’t an Input ….

Be something other than a packet trace

down times for BGP peers?

byte counts per unit time?

Use more information from the trace

encoding source and destination prefixes?

power levels on wireless?

dimensional signals?

Be properly documented in the paper…

Final Thoughts

Having put a lot of challenges on the table, let me
say we’ve also come a long way in a short time

Lots of interesting work, which you’ll hear over the
next few days

I encourage you to view it all (no matter how
impressive) as a starting point….

A final challenge:

Why are we using signal processing only for analysis?

Are there applications we could transform with signal
processing? (Beyond covert channels)