Figure 16-2: Dependence of average queuing delay on traffic intensity in Java

Encode QR Code ISO/IEC18004 in Java Figure 16-2: Dependence of average queuing delay on traffic intensity
Figure 16-2: Dependence of average queuing delay on traffic intensity
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Packet Loss
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Delay and Loss in Packet-Switched Networks
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In our discussions above, we have assumed that the queue is capable of holding an infinite number of packets In reality a queue preceding a link has finite capacity, although the queuing capacity greatly depends on the switch design and cost Because the queue capacity is a finite, packet delays do not really approach infinity as the traffic intensity approaches one Instead, a packet can arrive to find a full queue With no place to store such a packet, a router will drop that packet; that is, the packet will be lost From an end-system viewpoint, this will look like a packet having been transmitted into the network core, but never emerging from the network at the destination The fraction of lost packets increases as the traffic intensity increases Therefore, performance at a node is often measured not only in terms of delay, but also in terms of the probability of packet loss As we shall discuss in the subsequent chapters, a lost packet may be retransmitted on an end-to-end basis, by either the application or by the transport layer protocol
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End-to-End Delay
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Our discussion up to this point has been focused on the nodal delay, ie, the delay at a single router Let us conclude our discussion by briefly considering the delay from source to destination To get a handle on this concept, suppose there are Q-1 routers between the source host and the destination host Let us also suppose that the network is uncongested (so that queuing delays are negligible), the processing delay at each router and at the source host is dproc, the transmission rate out of each router and out of the source host is R bits/sec, and the propagation delay between each pair or routers and between the source host and the first router is dprop The nodal delays accumulate and give an end-to-end delay, dendend = Q (dproc + dtrans + dprop) , where once again dtrans = L/R, where L is the packet size We leave it to the reader to generalize this formula to the case of heterogeneous delays at the nodes and to the presence of an average queuing delay at each node
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Return to Table Of Contents
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References
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[Bertsekas 1992] D Bertsekas and R Gallager, Data Networks, 2nd Edition, Prentice Hall, Englewood Cliffs, NJ, 1992 [Daigle 1991] JN Daigle, Queuing Theory for Telecommunications, Addision-Wesley, Reading Massachusetts, 1991 [Kleinrock 1975] L Kleinrock, Queuing Systems, Volume 1, John Wiley, New York, 1975 [Kleinrock 1976] L Kleinrock, Queuing Systems, Volume 2, John Wiley, New York, 1976
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Delay and Loss in Packet-Switched Networks
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[Ross 1995] KW Ross, Multiservice Loss Models for Broadband Telecommunication Networks, Springer, Berlin, 1995
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Copyright Keith W Ross and James F Kurose 1996-2000
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Protocol Layers and Their Service Models
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17 Protocol Layers and Their Service Models
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From our discussion thus far, it is apparent that the Internet is an extremely complicated system We have seen that there are many "pieces" to the Internet: numerous applications and protocols, various types of end systems and connections between end systems, routers, and various types of link-level media Given this enormous complexity, is there any hope of organizing network architecture, or at least our discussion of network architecture Fortunately, the answers to both questions is "yes" Before attempting to organize our thoughts on Internet architecture, let's look for a human analogy Actually, we deal with complex systems all the time in our every day life Imagine if someone asked you to describe, for example, the airline system How would you find the structure to describe this complex system that has ticketing agents, baggage checkers, gate personnel, pilots and airplanes, air traffic control, and a worldwide system for routing airplanes One way to describe this system might be to describe the series of actions you take (or others take for you) when you fly on an airline You purchase your ticket, check your bags, go to the gate and eventually get loaded onto the plane The plane takes off and is routed to its destination After your plane lands, you de-plane at the gate and claim your bags If the trip was bad, you complain about the flight to the ticket agent (getting nothing for your effort) This scenario is shown in Figure 17-1
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Figure 17-1: Taking an airplane trip: actions Already, we can see some analogies here with computer networking: you are being shipped from source to destination by the airline; a packet is shipped from source host to destination host in the Internet But this is not quite the analogy we are after We are looking for some structure in Figure 17-1 Looking at Figure 17-1, we note that there is a ticketing function at each end; there is also a baggage function for already ticketed passengers, and a gate function for already-ticketed and alreadybaggage-checked passengers For passengers who have made it through the gate (ie, passengers who are already ticketed, baggage-checked, and through the gate), there is a takeoff and landing function, and while in flight, there is an airplane routing function This suggests that we can look at the functionality in Figure 17-1 in a horizontal manner, as shown in Figure 17-2
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