A Data Plane native PPV PIE Active Queue Mangement Scheme using P4 on a Programmable Switching ASIC

University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

Author: Love Dahlberg; [2021]

Keywords: AQM; PIE; PPV; P4; Tofino;

Abstract: New internet services require low and stable latency, which is difficult to provide with traditional routers and queuing mechanisms. Current routers aim to provide high throughput using large buffers causing considerable network latency under load. Recently, Active Queue Management (AQM) algorithms have been proposed to reduce such problem by actively controlling queue lengths to maintain target latencies. However, AQMs are difficult to implement in switching Application-Specific Integrated Circuits (ASIC) due to inherent architectural constraints. On the other hand, resource sharing is another important goal aiming to differentiate traffic and allocating more resources to different traffic types.  The objective of this thesis is to implement the AQM algorithm Proportional Integral Controller Enhanced (PIE) with a packet marking based resource sharing concept Per Packet Value (PPV) on a programmable switching ASIC using the novel network programmability concept P4. Our solution is designed to maintain low and controllable latency and to utilize the bottleneck link efficiently, while observing the bandwidth sharing properties of the marking scheme. Our goal is to show that Data Plane native implementations of PPV PIE using the Tofino is possible without severely limiting performance or accuracy. The solution places the computation of PIE's drop probability estimation on a timer in the Data Plane utilizing a state machine, packet mirroring, packet recirculation and approximative arithmetics implemented by lookup tables. Additionally, a small control loop is required in order to update lookup tables based on packet statistics from the Control Plane.  In our evaluation using a Tofino based testbed, we evaluate the impact of different parameters on both Control Plane latency, Data Plane throughput and delay for both static and dynamic traffic scenarios. Our results demonstrate commendable performance in terms of controlling queuing delay, effective throughput and bandwidth share when taking operator policy in regard.

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