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Accelerating Protocol Oblivious Forwarding Programmable Data Plane With Flow Cache

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The advances in software-defined networking (SDN) have recently promoted the development of Programmable Data Planes (PDP). PDP is famous in various network environments that need to support new protocols due… Click to show full abstract

The advances in software-defined networking (SDN) have recently promoted the development of Programmable Data Planes (PDP). PDP is famous in various network environments that need to support new protocols due to its flexibility and protocol independence. Protocol-oblivious forwarding (POF) is an implementation of PDP that uses to describe the match fields and mixes the protocol parsing into the pipeline, so there is no need for a pre-defined packet header parser. Current cache schemes for the data plane, such as Microflow Cache/Megaflow Cache, are primarily implemented based on the pre-defined packet header parser. In this paper, we first analyzed the two difficulties of generating cache tables on POF PDP. Then we analyzed the advantages and disadvantages of the single flow table cache system and multiple flow tables cache system from the perspective of time overhead. Finally, we propose a pipeline-oriented cache system to accelerate POF PDP. Aiming at the pipeline with multiple branches and multiple matching paths, we design algorithms to obtain all cache tables. Then our design leveraged the incremental calculation feature of the hash function to reduce the time overhead of cache lookup. In addition, the sorting mechanism and sleep mechanism for multiple cache tables were proposed according to the locality of traffic. Our design is implemented in a real POF PDP environment. The experimental results show that our pipeline-oriented cache scheme can effectively accelerate the programmable data plane, reducing packet forwarding latency and improving the throughput.

Keywords: protocol oblivious; programmable data; cache; data plane

Journal Title: IEEE Transactions on Network and Service Management
Year Published: 2023

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