Random Early Detection RED

TCP uses a windowing protocol, which restricts the amount of data a TCP sender can send without an acknowledgment. Each TCP window for each different TCP connection grows and shrinks based on many factors. RED works under the assumption that if some of the TCP connections can be made to shrink their windows before output queues fill, the collective number of packets sent into the network will be smaller, and the queue will not fill. During times when the queues are not getting very full, RED does not bother telling the TCP senders to slow down, because there is no need to slow down.

RED just discards some packets before a queue gets full and starts to tail drop. You can almost think of RED tools as managing the end of a queue, while the queuing tool manages the front of the queue! Because most traffic is TCP based and TCP slows down sending packets after a earlier packet is lost, RED reduces the load of packets that are entering the network before the queues fill. RED requires a fairly detailed explanation for a true understanding of what it does, and how it works. However, the general idea can be easily understood, as long as you know that TCP will slow down sending, by reducing its window size, when packets are lost.

TCP uses a window, which defines how much data can be sent before an acknowledgment is received. The window changes size dynamically, based on several factors, including lost packets. When packets are lost, depending on other conditions, a TCP window shrinks to 50 percent of the previous window size. With most data traffic being TCP in a typical network, when a large amount of tail drop occurs, almost all, if not all TCP connections sending packets across that link have their TCP windows shrunk by 50 percent at least once.

Consider the example in Figure 1-15. As that figure shows, 50 packets were sent, and the queue filled, and 10 of those packets were lost. If those 50 packets were part of 10 different TCP connections, and all 10 connections lost packets in the big tail drop, the next time the hosts send, only 25 total packets would be sent (windows all cut in half).

With RED, before tail drop occurs, RED discards some packets, forcing only a few of the TCP connections to slow down. By allowing only a few of the TCP windows to be reduced, tail drops can be avoided, and most users get better response time. The collective TCP sending rate stabilizes to a level for which tail drops seldom if ever occur. For those TCP connections for which RED dropped packets, response time is temporarily slow. However, that is much better than all users experiencing slow response time!

Queuing accomplishes a lot of tasks—including reducing loss. Because loss occurs when queues fill, and because the queuing methods typically provide the ability to configure the maximum queue size, you can just make the queue longer. With a longer maximum queue size, likelihood of loss decreases. However, queuing delay increases. Consider, for instance, Figure 1-16.

Figure 1-16 Queuing Affects on Packet Loss

Queue1—Size 50— Less Loss, More Latency

In the top example, a single FIFO queue is used. For delay-sensitive traffic, waiting behind 49 other packets might not work well. For applications that are loss sensitive, but not as delay sensitive, however, a long queue might work better. One goal might be to put delay-sensitive traffic into a different queue from loss-sensitive traffic, with an extra-long queue length for the loss-sensitive traffic, as shown in the bottom part of the figure. As usual, a tradeoff occurs—in this case, between low loss and low delay.

Table 1-9 summarizes the points concerning the two types of QoS tools that affect loss.

Table 1-9 QoS Tools That Affect Loss

Table 1-9 summarizes the points concerning the two types of QoS tools that affect loss.

Table 1-9 QoS Tools That Affect Loss

Type of QoS Tool

Brief Description


Implementing longer queues increases delay, but avoids loss.


Implementing RED drops packets randomly as queues approach the point of being full, slowing some TCP connections. This reduces overall load, shorten

ing the congested queue, while affecting only some user's response times.

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