H3C Technologies H3C S6300 Series Switches - Manual (Page 62)

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Configuring congestion avoidance
Overview
Avoiding congestion before it occurs is a proactive approach to improving network performance. As a
flow control mechanism, congestion avoidance actively monitors network resources (such as queues and
memory buffers), and drops packets when congestion is expected to occur or deteriorate.
When dropping packets from a source end, it cooperates with the flow control mechanism (such as TCP
flow control) at the source end to regulate the network traffic size. The combination of the local packet
drop policy and the source-end flow control mechanism helps maximize throughput and network use
efficiency and minimize packet loss and delay.
Tail drop
Congestion management techniques drop all packets that are arriving at a full queue. This tail drop
mechanism results in global TCP synchronization. If packets from multiple TCP connections are dropped,
these TCP connections go into the state of congestion avoidance and slow start to reduce traffic, but
traffic peak occurs later. Consequently, the network traffic jitters all the time.
RED and WRED
You can use Random Early Detection (RED) or Weighted Random Early Detection (WRED) to avoid
global TCP synchronization.
Both RED and WRED avoid global TCP synchronization by randomly dropping packets. When the
sending rates of some TCP sessions slow down after their packets are dropped, other TCP sessions
remain at high sending rates. Link bandwidth is efficiently used, because TCP sessions at high sending
rates always exist.
The RED or WRED algorithm sets an upper threshold and lower threshold for each queue, and processes
the packets in a queue as follows:
• When the queue size is shorter than the lower threshold, no packet is dropped;
• When the queue size reaches the upper threshold, all subsequent packets are dropped;
• When the queue size is between the lower threshold and the upper threshold, the received packets
are dropped based on the user-configured drop probability.
If the current queue size is compared with the upper threshold and lower threshold to determine the drop
policy, burst traffic is not fairly treated. To solve this problem, WRED compares the average queue size
with the upper threshold and lower threshold to determine the drop probability.
The average queue size reflects the queue size change trend but is not sensitive to burst queue size
changes, and burst traffic can be fairly treated.