Advancing discovery in many scientific fields depends crucially on our ability to extract the wealth of knowledge buried in massive datasets whose scale and complexity continue to grow exponentially with time. In order to address this fundamental challenge, this project aims to develop and deploy SANDIE, a Named Data Networking (NDN) architecture supported by advanced Software Defined Network services for Data Intensive Science, with the Large Hadron Collider (LHC) high energy physics program as the leading use case.

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