Beyond the Basics: An In-Depth Analysis and Multidimensional Survey of Programmable Switch in Software-Defined Networking

• Published in: The International journal of networked and distributed computing (Online) Vol. 13; no. 1
• Main Authors: Shirsath, Vaishali A., Chandane, Madhav M.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.06.2025
• Subjects: Computer Science; Review Article; P4; Programmable switches; PISA switches; P4 programming; Programmable data-planes; P4 language; Programmable IXP network; P4-enabled SDN; API; P4 runtime
• ISSN: 2211-7938; 2211-7946
• DOI: 10.1007/s44227-024-00049-6

The development of the programmable switch in software-defined networks (SDNs) is known for its rapid technological advancements. This growing domain has a wealth of information available on the topic, which has been collated and critically examined by many survey papers. However, previous survey papers mainly classified existing literature into predefined groups, lacking a comprehensive and distinct categorization. In contrast, this survey paper systematically analyses the last six years of literature into broad groups defined by their shared themes, methods, and technological aspects. The structured approach adopted in this paper offers a clear perspective on how the programmable data plane field has evolved. The key findings reveal significant progress in the programmable data plane in SDN, highlighting literature trends, citations, and author collaboration patterns. The incorporation of bibliometric analysis, which has hitherto not appeared in any survey, highlights the literature’s impact and reach. This analysis reveals that the average citations per publication peaked in the early years (2018–2019), with values as high as 13.0, indicating early enthusiasm in the field, followed by a gradual normalization as the research progressed. Furthermore, a substantial 46% of the included literature demonstrated significant impact and relevance in the field. The survey adopts a statistical and diagrammatic approach to enhance understanding of the evolution and interconnections in programmable data planes, decoding complex information into more comprehensible formats. Ultimately, this work can serve as a valuable resource for understanding the dynamic landscape of programmable data planes, highlighting key contributions, and setting directions for future research.