mirror of
https://github.com/AuxXxilium/linux_dsm_epyc7002.git
synced 2025-02-06 05:45:20 +07:00
78dc70ebaa
Aggregation effects are extremely common with wifi, cellular, and cable
modem link technologies, ACK decimation in middleboxes, and LRO and GRO
in receiving hosts. The aggregation can happen in either direction,
data or ACKs, but in either case the aggregation effect is visible
to the sender in the ACK stream.
Previously BBR's sending was often limited by cwnd under severe ACK
aggregation/decimation because BBR sized the cwnd at 2*BDP. If packets
were acked in bursts after long delays (e.g. one ACK acking 5*BDP after
5*RTT), BBR's sending was halted after sending 2*BDP over 2*RTT, leaving
the bottleneck idle for potentially long periods. Note that loss-based
congestion control does not have this issue because when facing
aggregation it continues increasing cwnd after bursts of ACKs, growing
cwnd until the buffer is full.
To achieve good throughput in the presence of aggregation effects, this
algorithm allows the BBR sender to put extra data in flight to keep the
bottleneck utilized during silences in the ACK stream that it has evidence
to suggest were caused by aggregation.
A summary of the algorithm: when a burst of packets are acked by a
stretched ACK or a burst of ACKs or both, BBR first estimates the expected
amount of data that should have been acked, based on its estimated
bandwidth. Then the surplus ("extra_acked") is recorded in a windowed-max
filter to estimate the recent level of observed ACK aggregation. Then cwnd
is increased by the ACK aggregation estimate. The larger cwnd avoids BBR
being cwnd-limited in the face of ACK silences that recent history suggests
were caused by aggregation. As a sanity check, the ACK aggregation degree
is upper-bounded by the cwnd (at the time of measurement) and a global max
of BW * 100ms. The algorithm is further described by the following
presentation:
https://datatracker.ietf.org/meeting/101/materials/slides-101-iccrg-an-update-on-bbr-work-at-google-00
In our internal testing, we observed a significant increase in BBR
throughput (measured using netperf), in a basic wifi setup.
- Host1 (sender on ethernet) -> AP -> Host2 (receiver on wifi)
- 2.4 GHz -> BBR before: ~73 Mbps; BBR after: ~102 Mbps; CUBIC: ~100 Mbps
- 5.0 GHz -> BBR before: ~362 Mbps; BBR after: ~593 Mbps; CUBIC: ~601 Mbps
Also, this code is running globally on YouTube TCP connections and produced
significant bandwidth increases for YouTube traffic.
This is based on Ian Swett's max_ack_height_ algorithm from the
QUIC BBR implementation.
Signed-off-by: Priyaranjan Jha <priyarjha@google.com>
Signed-off-by: Neal Cardwell <ncardwell@google.com>
Signed-off-by: Yuchung Cheng <ycheng@google.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
|
||
|---|---|---|
| .. | ||
| 6lowpan | ||
| 9p | ||
| 802 | ||
| 8021q | ||
| appletalk | ||
| atm | ||
| ax25 | ||
| batman-adv | ||
| bluetooth | ||
| bpf | ||
| bpfilter | ||
| bridge | ||
| caif | ||
| can | ||
| ceph | ||
| core | ||
| dcb | ||
| dccp | ||
| decnet | ||
| dns_resolver | ||
| dsa | ||
| ethernet | ||
| hsr | ||
| ieee802154 | ||
| ife | ||
| ipv4 | ||
| ipv6 | ||
| iucv | ||
| kcm | ||
| key | ||
| l2tp | ||
| l3mdev | ||
| lapb | ||
| llc | ||
| mac80211 | ||
| mac802154 | ||
| mpls | ||
| ncsi | ||
| netfilter | ||
| netlabel | ||
| netlink | ||
| netrom | ||
| nfc | ||
| nsh | ||
| openvswitch | ||
| packet | ||
| phonet | ||
| psample | ||
| qrtr | ||
| rds | ||
| rfkill | ||
| rose | ||
| rxrpc | ||
| sched | ||
| sctp | ||
| smc | ||
| strparser | ||
| sunrpc | ||
| switchdev | ||
| tipc | ||
| tls | ||
| unix | ||
| vmw_vsock | ||
| wimax | ||
| wireless | ||
| x25 | ||
| xdp | ||
| xfrm | ||
| compat.c | ||
| Kconfig | ||
| Makefile | ||
| socket.c | ||
| sysctl_net.c | ||