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RWTH Aachen
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Automatic Provenance Generation for Serverless Computing

Thesis type
  • Master
Status Open
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In the context of this work, the student should extend the Function-as-a-Service (FaaS) paradigm of serverless computing with concepts for the automatic tracking of provenance information (information about data origins, uses, actors and involved processes over time, similar to a GIT revision history for data) and implement a corresponding framework using a readily available FaaS platform, such as Kubeless, OpenFaaS or the Fn Project.

In the Internet of Things, and especially the Internet of Production, massive amounts of semi-structured data, such as sensor readings, process control data, log data etc., are generated at an ever increasing pace. While this data is abundant, extracting information from these source is typically hard due to the lack of semantic interpretability of the data, further rendering information sharing across organizational boundaries practically infeasible. Especially the lack of versioning information, data origins and influences renders interorganizational collaboration practically infeasible.

Recently, cloud computing and other relatively novel computational paradigms have been explored in manufacturing environments (c.f. e.g. https://books.google.de/books?id=F119DwAAQBAJ). While such approaches appear promising for the future of an Internet of Production, reusability and interoperability of the proposed approaches is limited by the lack of a common computing model.

In the context of this work, the student should extend the Function-as-a-Service (FaaS) paradigm of serverless computing with concepts for the automatic tracking of provenance information or data lineage (information about data origins, uses, actors and involved processes over time, similar to a GIT revision history for data) and implement a corresponding framework using a readily available FaaS platform, such as Kubeless, OpenFaaS or the Fn Project.

If you are interested in this thesis, a related topic or have additional questions, please do not hesitate to send a message to gleim@dbis.rwth-aachen.de

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