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Details of Grant 

EPSRC Reference: EP/T007206/1
Title: NEAT: NEtwork dATa plane measurements as first class primitive
Principal Investigator: Antichi, Dr G
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Barefoot Networks Cisco European Lab for Particle Physics - CERN
VMware
Department: Sch of Electronic Eng & Computer Science
Organisation: Queen Mary University of London
Scheme: New Investigator Award
Starts: 01 January 2020 Ends: 31 December 2022 Value (£): 394,776
EPSRC Research Topic Classifications:
Networks & Distributed Systems
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
10 Jul 2019 EPSRC ICT Prioritisation Panel July 2019 Announced
Summary on Grant Application Form
Data centre networks are poorly equipped to rapidly spot and address failures, resulting in countless well-documented application performance degradation or outages. This is because the investigation process is performed in centralised commodity servers (collectors) that do not have per-packet visibility, but instead aggregated and sampled statistics from the data plane. The NEAT project will address this deficiency by moving traffic analysis directly into switches that have per-packet visibility. Exploiting advances in programmable hardware, e.g. P4, NEAT will rethink data plane operation and will transform switches from just packet forwarder with limited monitoring capabilities to more intelligent systems capable of analysing traffic and exporting only relevant results. This will enable the level of fine-grained data plane visibility required to allow operators to rapidly identify and adapt to changes in network conditions, which hurts applications.
Key Findings
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