The Programmable Data Plane: Abstractions, Architectures, Algorithms, and Applications
arXiv:2110.00631 · doi:10.1145/3447868
Abstract
Programmable data plane technology enables the systematic reconfiguration of the low-level processing steps applied to network packets and is a key driver in realizing the next generation of network services and applications. This survey presents recent trends and issues in the design and implementation of programmable network devices, focusing on prominent architectures, abstractions, algorithms, and applications proposed, debated, and realized over the past years. We elaborate on the trends that led to the emergence of this technology and highlight the most important pointers from the literature, casting different taxonomies for the field and identifying avenues for future research.
References in corpus (10)
- TensorFlow: A system for large-scale machine learning
- Network Slicing for 5G with SDN/NFV: Concepts, Architectures and Challenges
- Software-Defined and Virtualized Future Mobile and Wireless Networks: A Survey
- Open Packet Processor: a programmable architecture for wire speed platform-independent stateful in-network processing
- Compressing IP Forwarding Tables: Towards Entropy Bounds and Beyond
- In-network Neural Networks
- SNAP: Stateful Network-Wide Abstractions for Packet Processing
- Dapper: Data Plane Performance Diagnosis of TCP
- Gauntlet: Finding Bugs in Compilers for Programmable Packet Processing
- MTS: Bringing Multi-Tenancy to Virtual Networking