Traffic Management for High-Speed Networks
Network congestion will increase as network speed increases. New control methods are needed, especially for handling "bursty" traffic expected in very high speed networks such as asynchronous transfer mode (ATM) networks. Users should have instant access to all available network bandwidth when they need it, while being assured that the chance of losing data in the presence of congestion will be negligible. At the same time, high network utilization must be achieved, and services requiting guaranteed performance must be accommodated. This paper discusses these issues and describes congestion control solutions under study at Harvard University and elsewhere. Motivations, theory, and experimental results are presented.
Over the past decade, the speed of computer and telecommunications networks has improved substantially. To wit:
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1.5-Mbps (megabits per second) T1 |
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4- or 16-Mbps Token Rings |
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10-Mbps Ethernet |
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45-Mbps T3 |
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100-Mbps Ethernet |
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100-Mbps FDDI |
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155-Mbps OC-3 ATM |
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622-Mbps OC-12 ATM |
This rapid growth in speed is expected to continue over the next decade, because many new applications in important areas such as data and video will demand very high network bandwidths. These high-speed networks are introducing major new challenges in network congestion control, as explained in the next two sections. That the high-speed networks would make the solution for network congestion harder is contrary to what one's intuition might suggest.
Any network has bottlenecks or congestion points, i.e., locations where more data may arrive than the network can carry. A common cause for congestion is a mismatch in speed between networks. For example, a typical high-performance local area network (LAN) environment in the next several years may have the architecture shown in Figure 1. While the servers will use new high-speed asynchronous transfer mode (ATM) connections at the OC-3 rate of 155 Mbps, many clients will still depend on old, inexpensive but slower, 10-Mbps Ethernet connections. Data flowing from the servers at 155 Mbps to the clients at 10 Mbps will experience congestion at the interface between the ATM and Ethernet networks.
Congestion can also occur inside a network node that has multiple ports. Such a node can be a switch such as an ATM switch or a gateway such as a router. As depicted in Figure 2, congestion arises when data, destined for a single output port, arrive at many different input ports. The faster and more numerous these input ports are, the severer the congestion will be.
A consequence of congestion is the loss of data due to buffer overflow. For data communications in which every bit must be transmitted correctly, lost data will have to be retransmitted, and will result in degraded network utilization and increased communications delay for end users.
A universal solution to the problem of losing data because of congestion involves buffer memory in which a congested point can temporarily queue data directed at overloaded output ports. This use of buffer is illustrated in Figure 2. However, simply providing large buffers would likely incur prohibitively high memory cost for high-speed networks, because as network speed increases, so also will the following factors:
Figure 1
Congestion due to a mismatch in speed between 155-Mbps ATM network and 10-Mbps Ethernet.
Figure 2
Congestion, in a switch or gateway, due to multiple arrivals at the same output.
To prevent data loss due to congestion, network buffers could be increased to accommodate the increase in each of the above factors. But these factors increase independently, and the multiplicative effects of such increases will demand enormously large buffers. In addition, as network usage increases, so also will the expected number of active sessions on the network and their peak bandwidths. For each session, a network node may have to buffer all the on-the-fly data from a distant sending host to itself when congestion occurs. The buffers occupied by the session can be the entire TCP window if TCP is used. If there are N sessions, N times the size/capacity of this buffer will be needed.
For all these reasons, brute-force methods of using larger and larger buffers cannot solve the congestion problems to be expected with high-speed networks.