Design and Implementation of Programmable Data Plane Supporting Multiple Data Types
Software-defined networking (SDN) separates the control plane and the data plane, which provides network applications with global network topology and the flexibility to customize packet forwarding rules. SDN has a wide range of innovative applications in 5G, Internet of Things, and information cent...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
MDPI AG
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/bf5fe761a5c64a1096b39763c771bb1c |
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| Sumario: | Software-defined networking (SDN) separates the control plane and the data plane, which provides network applications with global network topology and the flexibility to customize packet forwarding rules. SDN has a wide range of innovative applications in 5G, Internet of Things, and information center networks. However, the match-action programming model represented by OpenFlow/Protocol Oblivious Forwarding (POF) in SDN can only process limited types of data such as packets and metadata, making it hard to fulfill future network applications. In this paper, data type and data location are added in the matching fields and actions to make the match-action table (MAT) compatible with multiple types of data, hence improving the data plane’s programmability. Data type helps the MAT to perceive multiple types of data, allowing them to be processed by a single MAT. Data location allows MAT to be decoupled from data meaning, quickly locating specific data in the switch. Based on Intel’s Data Plane Development Kit (DPDK), we design and implement a pipeline that is compatible with multiple types of data processing. Protocol and data type oblivious match-action tables and atomic instructions are included in the pipeline. Experiments show that representing data with data type and data location makes the pipeline compatible with multiple types of data without sacrificing forwarding performance, fulfilling the needs of network applications to handle a variety of types of data while avoiding repeating hardware design. |
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