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Software used to prepare the last-mile dataset and Jupyter notebooks used for analysis.

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Dissecting Last-mile Latency Characteristics →
ACM SIGCOMM Computer Communication Review →
October 2017


Dataset

The raw dataset is available here →

It includes the SQL schema lastmile.sql and the dataset in sqlite3 format lastmile.db

Installation

make will install the python dependencies required to run the jupyter notebooks. make run will run jupyter.

Repeating the results

plot-* notebooks can be used to repeat the analysis on the existing dataset. Each such notebook produces a single plot in the paper.

Reproducing the results

make db will bootstrap a new database using the lastmile.sql schema. db-insert-* notebooks can be used to fill in the dataset. Each such notebook fills in entries in one table. This includes mechanics to provision measurements on RIPE Atlas, fetch measurement results and dump them in the database tables while also augmenting the metadata with third-party datasets such as peeringDB and RIPE stat APIs. Once all the tables are filled in plot-* can be used to reproduce results on a different dataset.

Contact

Please feel welcome to contact the authors for further details.

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Software used to prepare the last-mile dataset and Jupyter notebooks used for analysis.

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