mlsanityData to 7 Oct 2026

Programming Protocol-Independent Packet Processors

arXiv 1312.1719 ↗First posted 5 Dec 2013cs.NIcited by 21

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Abstract (arXiv)

P4 is a high-level language for programming protocol-independent packet processors. P4 works in conjunction with SDN control protocols like OpenFlow. In its current form, OpenFlow explicitly specifies protocol headers on which it operates. This set has grown from 12 to 41 fields in a few years, increasing the complexity of the specification while still not providing the flexibility to add new headers. In this paper we propose P4 as a strawman proposal for how OpenFlow should evolve in the future. We have three goals: (1) Reconfigurability in the field: Programmers should be able to change the way switches process packets once they are deployed. (2) Protocol independence: Switches should not be tied to any specific network protocols. (3) Target independence: Programmers should be able to describe packet-processing functionality independently of the specifics of the underlying hardware. As an example, we describe how to use P4 to configure a switch to add a new hierarchical label.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Dec 2013.

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Citing papers per year: 2021: 2; 2022: 4; 2023: 0; 2024: 5; 2025: 5; 2026: 5.

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  1. 2021Applications and Techniques for Fast Machine Learning in Sciencecited by 32
  2. 2024Brain-on-Switch: Towards Advanced Intelligent Network Data Plane via NN-Driven Traffic Analysis at Line-Speedcited by 5
  3. 2022IIsy: Practical In-Network Classificationcited by 3
  4. 2026DarwinNet: An Evolutionary Network Architecture for Agent-Driven Protocol Synthesiscited by 3
  5. 2025Pegasus: A Universal Framework for Scalable Deep Learning Inference on the Dataplanecited by 2
  6. 2024FRED: Flexible REduction-Distribution Interconnect and Communication Implementation for Wafer-Scale Distributed Training of DNN Modelscited by 1
  7. 2025UniNet: A Unified Multi-granular Traffic Modeling Framework for Network Securitycited by 1
  8. 2021Revelio: ML-Generated Debugging Queries for Distributed Systemscited by 0
  9. 2022Network Programming via Computable Productscited by 0
  10. 2022Automating In-Network Machine Learningcited by 0
  11. 2022Learning Failure-Inducing Models for Testing Software-Defined Networkscited by 0
  12. 2024Prose-to-P4: Leveraging High Level Languagescited by 0
9 more
  1. 2024Accelerating Stateful Network Applications with Performance Prediction on SoC SmartNICscited by 0
  2. 2024Inference-to-complete: A High-performance and Programmable Data-plane Co-processor for Neural-network-driven Traffic Analysiscited by 0
  3. 2025Proof of Humanity: A Multi-Layer Network Framework for Certifying Human-Originated Content in an AI-Dominated Internetcited by 0
  4. 2025Reinforcement Learning-based Adaptive Path Selection for Programmable Networkscited by 0
  5. 2025Serve Programs, Not Promptscited by 0
  6. 2026Chimera: Neuro-Symbolic Attention Primitives for Trustworthy Dataplane Intelligencecited by 0
  7. 2026Tiara: A Programmable Line-Rate ISA for Remote Memory Accesscited by 0
  8. 2026Decode-Time Grammars: Constrained LLM Generation over a Refinement Order of Grammar Fragmentscited by 0
  9. 2026Can AI Agents Detect and Repair Artifact Drift in Network Experiments?cited by 0