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Distance vector protocols have that name because of the way they work. Recovering physicists will remember that a vector is a measure of something that has both direction and magnitude associated with it. The name is appropriate in this case, because the routing protocol optimizes on a direction (port number) and a magnitude (hop count). Because networks are growing larger, traffic routinely encounters route solutions with large hop counts. This reduces the effectiveness of distance vector solutions. A better solution is the link state protocol. Instead of transmitting entire routing tables on a scheduled basis, link state protocols use a technique called flooding to only transmit changes that occur to adjacent devices as they occur. This results in less congestion and a more efficient use of network resources, and it reduces the impact of multiple hops in large-scale networks. Both distance vector and link state protocols are in widespread use today. The most common distance vector protocols are the Routing Information Protocol (RIP) and Cisco s Interior Gateway Routing Protocol (IGRP) and Border Gateway Protocol (BGP). Link state protocols include Open Shortest Path First (OSPF), commonly used on the Internet, as well as the Netware Link Services Protocol (NLSP), used to route Internetwork Packet Exchange (IPX) traffic. Clearly, both connection-oriented and connectionless transport techniques, as well as their related routing protocols, have a place in the modern telecommunications arena. As QoS becomes such a critical component of the service offered by network providers, the importance of both routing and congestion control becomes apparent. We now turn our attention to the second area of responsibility at the network layer, congestion control.
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At its most fundamental level, congestion control is a mechanism for reducing the volume of traffic on a particular route through some form of load-balancing. No matter how large, diverse, or capable a network is, some degree of congestion is inevitable. It can result from sudden unexpectedly high utilization levels in one area of the network, from failures of network components, or from poor engineering. In the telephone network, for example, the busiest calling day of the year in the United States is Mother s Day. To reduce the probability that a caller will not be able to complete a call to Mom, network traffic engineers take extraordi-
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nary steps to load-balance the network. For example, when subscribers on the East Coast are making long-distance calls at 9:00 in the morning, West Coast subscribers haven t even turned on their latte machines yet. Network resources in the West are underutilized during that period, so engineers route East Coast traffic westward and then hairpin it back to its destination to spread the load across the entire network. As the day gets later, they reduce the volume of westward-bound traffic to ensure that California has adequate network resources for its own calls. Two terms are important in this discussion. One is congestion; the other is delay. The terms are often used interchangeably, but they are not the same thing. Years ago I lived in the San Francisco area where traffic congestion is a way of life. I often had to drive across the many bridges that criss-cross San Francisco Bay, the Suisun Straits, or the Sacramento River. Many of those bridges require drivers to stop and pay a toll, resulting in localized delay. The time it takes to stop and pay the toll is mere seconds, yet traffic often backs up for miles as a result of this local phenomenon. This is the relationship between the two: local delay often results in widespread congestion, and congestion is usually caused by inadequate buffer or memory space. Increase the number of buffers the lanes of traffic on the bridge, if you will and congestion drops off. Open another line or two at Home Depot ( No waiting on line seven! ) and congestion drops off. The various players in the fast food industry manage congestion in different ways, and with dramatically different results. Without naming them, some use a single queue with a single server to take orders, a technique that works well until the lunch rush begins. Then things back up dramatically. Others use multiple queues with multiple servers, a technique that is better except that one queue can experience serious delays should someone place an order for a nonstandard item or try to pay with a credit card. That line then experiences serious delay. The most effective restaurants stole an idea from the airlines and use a single queue with multiple servers. This keeps things moving because the instant a server is available, the next person in line is served. Remember when Jeff Goldblum, the chaos theoretician in Jurassic Park, talked about the Butterfly Effect How a butterfly flapping its wings in the Amazon Basin can kick off a chain of events that affects weather patterns in New York City That aspect of Chaos Theory contributes greatly to the manner in which networks behave, and the degree to which their behavior is immensely difficult to predict under a load.
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