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[Ricky Mok]

Yes. The video is here. 
https://catalog.caida.org/details/media/2022_jitterbug_pam/resources

The code is on GitHub (https://github.com/estcarisimo/jitterbug). I am 
happy to help if you want to try it on your dataset.

Applying the method to all the data that we have is an option, as it is 
computationally expensive to run. But we currently don't have a concrete 
next step for this project (the funding for this was gone). We barely 
keep the data (MANIC) collection going at this stage.

Ricky

On 4/21/22 12:07, Dave Taht wrote:
> On Thu, Apr 21, 2022 at 11:44 AM Ricky Mok <cskpmok at caida.org> wrote:
>> Thanks Dave for creating and managing this mailing list!
> and: thank *you* (and kc, dave clark, et al)  for this really
> excellent paper on "jitterbug". Quality jitter metrics have long been
> lacking on the internet.
>
> https://link.springer.com/chapter/10.1007/978-3-030-98785-5_7
>
> "We discovered a set of features in jitter and jitter dispersion —a
> jitter-derived time series we define in this paper—time series that
> are characteristic of periods of congestion. We leverage these
> concepts to create a jitter-based congestion inference framework that
> we call Jitterbug. We apply Jitterbug’s capabilities to a wide range
> of traffic scenarios and discover that Jitterbug can correctly
> identify both recurrent and one-off congestion events. We validate
> Jitterbug inferences against state-of-the-art autocorrelation-based
> inferences of recurrent congestion. We find that the two approaches
> have strong congruity in their inferences, but Jitterbug holds promise
> for detecting one-off as well as recurrent congestion."
>
> It looks very promising. Is the code anywhere? Is the talk up?
>
> ... and where do you plan to go next with it? Are any other groups
> beginning to leverage it?
>
>> Ricky
>>