Exploring networks of the future

Evolving technological and social networks, intertwined and worldwide in scope, are rapidly transforming societies and economies. The Global Environment for Network Innovations (GENI), a project sponsored by the National Science Foundation, is open and broadly inclusive, providing collaborative and exploratory environments for academia, industry and the public to catalyze groundbreaking discoveries and innovation in these emerging global networks.

GENI is a virtual laboratory at the frontiers of network science and engineering for exploring future internets at scale. GENI creates major opportunities to understand, innovate and transform global networks and their interactions with society.

GENI NetKarma Enables Researchers to Tap Past Experiment Designs for Use in Current Work

Net Karma Team

Front Row: Beth Plale, Prajakta Purohit, Chris Small; Middle Row: Aparna Rao, Devarshi Ghoshal, You-Wei; Cheah Back Row: Girish Subramanian, Robert Ping, Yiming Sun

GENI NetKarma is now prototyping and trying out a “provenance registry” that will capture data about the design of GENI experiments and correlate it with historical data. The NetKarma project, led by PIs Beth Plale and Chris Small from the Indiana University School of Informatics, have been working with other GENI tool system developers such as the Gush and Raven projects to obtain provenance data including experiment tool commands, network topology, software versioning, and GENI operational status information.  NetKarma will explore concepts that may ultimately be used to create an “Experiment Definition Language.”  By providing all GENI network researchers access to the complete history of all experiments and data on the GENI network, GENI NetKarma will lead to more streamlined, robust, and productive experimentation.

GENI NetKarma will enable GENI experimenters to capture data about experiments including: time ordering and relationships within the experiment, changes made between runs, and relationships between the experiment and control framework.  Information collected includes the operational status of the experiment’s substrate/infrastructure, code and data used by the experiment, and annotations by the experimenters.  This data, called provenance data, can be used to reproduce experiments, mine patterns, and analyze experiments.

The NetKarma project has demonstrated the ingestion of provenance information from the Gush experiment control tool and the visualization of the provenance graph generated from this information.  The newest version of the gush2netkarma software parses Gush log files to obtain provenance information.  The project team is now starting to process logs from the Raven provisioning service to get information such as experiment node locations, time of deployment of software packages and versions of software deployed.

NetKarma is based on the Open Provenance Model (OPM), a community effort to standardize on a representation of provenance graphs.