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P4-enabled Network-assisted Congestion Feedback: A Case for NACKs Anja Feldmann Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli

Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

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Page 1: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

P4-enabled Network-assisted Congestion Feedback:

A Case for NACKs

Anja FeldmannBala Chandrasekaran, Emilia Weyulu, Seif Fathalli

Page 2: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

Motivation – some observations

• Buffers‣ Are getting shallow (relative to link speed)‣ Should be shallow to ensure short, deterministic delays

• Traffic ‣ Mice vs. Elephants‣ Elephants contribute most traffic – React to congestion signal‣ Mice contribute most flows – Not subject to congestion control‣ Separating mice from elephants can be beneficial

• Today’s switches

2MPI INF | Anja Feldmann

Page 3: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

Background – Buffer Occupancy

• NS2 simulations results• Mice can fill any queue as they

are not subject to congestion control

3MPI INF | Anja Feldmann

Server

Clients

Used to limit capacity1.5 Mbits to 3 Mbits

Used to vary delay640 ms or 40 ms

40-100 Kbits/second

Used to measure before bottleneck

Infinite sources Web like sources

Page 4: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

Motivation – some observations

• Buffers‣ Are getting shallow (relative to link speed)‣ Should be shallow to ensure short, deterministic delays

• Traffic ‣ Mice vs. Elephants‣ Elephants contribute most traffic – React to congestion signal‣ Mice contribute most flows – Not subject to congestion control‣ Separating mice from elephants can be beneficial

• Today’s switches ‣ Enable gathering of fine-grain statistics – The P4 advantage‣ Enable use of multiple queues – The QoS leftover

4MPI INF | Anja Feldmann

Page 5: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

Today‘s Congestion Inference

• Left to the end-systems

5MPI INF | Anja Feldmann

SourceDestination

Implicit(delay, discard)

Explicit(binary, rate)

Policing

Choke Packet

Back Pressure

Today

Today

Archaic

Archaic

Page 6: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

Tomorrow‘s Congestion Inference

• Network-assisted• Network-assisted Congestion Notification (NCF)

6MPI INF | Anja Feldmann

SourceDestinationNCF

Page 7: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

NCF – Insights

• Network (switches/routers) can initiate NACKs with P4 ‣ Trim packets in data plane‣ Reflect packet as NACK back to source

• Address elephants and mice‣ Detect elephants in data plane‣ Use separate queues

• Three queues suffice‣ Dynamically allocate memory (to keep buffers where needed)‣ Congestion signals independent of queue usage

7MPI INF | Anja Feldmann

Page 8: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

Network-assisted Congestion Feedback (NCF)

• Rolling Sketches (Counters)‣ How

- Rolling: Multiple time windows- Counters: Per flow per time window- Mice: Sum of counters < threshold- Elephant: Sum of counters > threshold

‣ Advantages- Small memory foot-print- Efficient and flexible- Feasible: Due to skewed flow distributions

8MPI INF | Anja Feldmann

Page 9: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

Advantages NCF

• Fast direct feedback directly to source(includes lost packet info)

• Separation of Mice and Elephants• Flexible allocation of buffer memory

• Design‣ Is work-conserving‣ Is scalable‣ Shares resources fairly‣ Ensures short queues‣ Can handle TCP Incast challenge‣ Incrementally deployable

9MPI INF | Anja Feldmann

SourceDestinationNCF

Page 10: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

Status

• Prototype implementations‣ P4‣ NS3

• First results look promising

• Needed: NCF enabled congestion control algorithm

10MPI INF | Anja Feldmann

Page 11: Anja Feldmann - Stanford Universitybuffer-workshop.stanford.edu/slides/bufferworkshop-feldmann.pdf · Anja Feldmann. Bala Chandrasekaran, Emilia Weyulu, Seif Fathalli. Motivation

NCF – Insights

• Network (switches/routers) can initiate NACKs with P4 ‣ Trim packets in data plane‣ Reflect packet as NACK back to source => Fast congestion feedback

• Separate elephants and mice‣ Detect elephants in data plane‣ Use separate queues

• Three queues suffice‣ Dynamically allocate memory (to keep buffers where needed)‣ Congestion signals independent of queue usage

11MPI INF | Anja Feldmann