A survey on data plane programming with P4: Fundamentals, advances, and applied research. (March 2023)

• Record Type: Journal Article
• Authors: Hauser, Frederik; Häberle, Marco; Merling, Daniel; Lindner, Steffen; Gurevich, Vladimir; Zeiger, Florian; Frank, Reinhard; Menth, Michael
• Is Part Of: Journal of network and computer applications. Volume 212(2023)
• Publication Date: 2023-03
• Subjects: P4 -- SDN -- Programmable data planes; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2022.103561
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: Programmable data planes allow users to define their own data plane algorithms for network devices including appropriate data plane application programming interfaces (APIs) which may be leveraged by user-defined software-defined networking (SDN) control. This offers great flexibility for network customization, be it for specialized, commercial appliances, e.g., in 5G or data center networks, or for rapid prototyping in industrial and academic research. Programming protocol-independent packet processors (P4) has emerged as the currently most widespread abstraction, programming language, and concept for data plane programming. It is developed and standardized by an open community, and it is supported by various software and hardware platforms. In the first part of this paper we give a tutorial of data plane programming models, the P4 programming language, architectures, compilers, targets, and data plane APIs. We also consider research efforts to advance P4 technology. In the second part, we categorize a large body of literature of P4-based applied research into different research domains, summarize the contributions of these papers, and extract prototypes, target platforms, and source code availability. For each research domain, we analyze how the reviewed works benefit from P4's core features. Finally, we discuss potential next steps based on our findings.