Assignment 3 Solutions 2/10/2012

Transcription

1 INFO334 / TELE302 Assignment 3 Solutions 2/10/2012 The WAN topology to be adopted for the enterprise WAN is shown in Figure 1. Figure 1: NZAM WAN topology. 1 Task 1: Reliability Analysis (4 marks) 1. What is the end-to-end reliability between Dunedin and Auckland? We have a chain structure DUD-CHC-WLG-AKL to work on. As explained in the lectures, we prefer to work with small numbers (of unavailability). For example, the 99% availability gives a 0.01 unavailability. The unavailability of a chain is as simple as the sum of unavailabilities of individual links(if they are small enough). Precisely, the equivalent unavailability between DUD-WLG should be = Going further with the WLG-AKL link, the unavailability for DUD-AKL is then = 0.021, which means the availability of DUD-AKL is =97.9%.

2 2. Using short and low-reliability links (99%), can we improve the DUD-AKL reliability? Find a cheap solution. To enhance the reliability on two ends (DUD-CHC and WLG-AKL), we can establish two extra 99% links for DUD-CHC and WLG-PMR, as shown in Figure 2. The following works out the unavailabilities: Figure 2: NZAM WAN topology. DUD-CHC equivalent: = ; CHC-WLG: 0.001; WLG-AKL equivalent: 0.01 ( ) ; DUD-AKL equivalent, summing up: = Therefore the new topology gives a DUD-AKL availability of 99.87%. Note that adding a direct WLG-AKL link instead would give the same result as a WLG-PMR link, but the latter is cheaper, and gives better reliability to PMR as well. 3. Where is the reliability bottleneck and to what level shall it be upgraded so that the DUD-AKL reliability can reach at least 99.9%? From the above analysis clearly the bottleneck lies at the CHC-WLG link and we need to reduce its unavailability down to (so that the sum becomes 0.001), i.e., the link s availability should be upgraded to 99.93%. 2

3 2 Task 2: Simulation (4 marks) Following the simple.tcl example, it s probably easier to plot out the topology horizontally, so it looks like the following: ############## topology ################ # H5 H4 H1 # \ \ / # R5 R4 R3 R1 H2 # / \ # H3 R2 ######################################## From the nam display as shown in Figure 3 (unfortunately the naming of the nodes is a bit out of control here - so hopefully you have managed to cope with that), it s obvious to see that the bottleneck is at Link R4-R3, where basically all packets get dropped. For some reason this effectively relieves Link R3-R1 and there is no further dropping from there! Figure 3: Simulation animation snapshot showing the WAN topology and packet drops. To deal with the CBR traffic that causes trouble, we have tried alternative disciplines for Link R4-R3, including RED and SFQ. This results in reduced packet drops and improved throughput during the rush hours where CBR traffic is active. 2.1 Packet drop comparison Depending on the queueing discipline chosen for Link R4-R3, the number of either CBR or TCP packet drops also varies, as summarized in Table 1. While SFQ achieved the lowest drop for TCP traffic, its CBR dropping is rather serious (in fact, almost one third are lost). DropTail gets the least dropping for CBR, but the significant amount of TCP drops. The RED seems to produce moderate CBR drops, which may be a good choice in maintaining the CBR quality. 3

4 Table 1: Number of packet drops. Discipline TCP drops CBR drops DropTail RED SFQ Throughput comparison To assess the true TCP performance, we need to verify the TCP throughput (in terms of number of TCP packets received at H1 per second). This can be visualized using the following command line: awk $1=="r"&&$4=="5"&&$5=="tcp"{print int($2)} out.tr uniq -c awk {print $2,$1} xgraph Figure 4 compares the throughput obtained when using DropTail, RED, and SFQ. Interestingly, during the rush hour SFQ performs the best, while RED also slightly outperforms DropTail. For an explanation we can check the congestion window of the TCP flows. In the simulation script, the monitoring of cwnd can be enabled, e.g., on Flow H3-H1, by using the following lines: s e t t r f [ open cwnd. t r w] $tcp1 attach $ t r f $tcp1 t r a c e cwnd Figure 5 reveals what happens with the TCP congestion window maintained for the H3-H1 flow. Despite more packet drops, RED copes with congestion better than DropTail does. 250 DropTail RED SFQ 200 # of TCP packets rcvd.) time (sec) Figure 4: TCP packets received by H1 over time using three disciplines: DropTail, RED, and SFQ on the R4-R3 link respectively. 4

5 60 DropTail RED SFQ cwnd Time (sec.) Figure 5: CWND variation of the H3-H1 TCP flow under DropTail, RED, and SFQ used by Link R4-R3 queue. Other queueing disciplines can also be considered, such as FQ and DRR (deficit round robin) - both of which further improve TCP throughput but let down CBR traffic. 2.3 Recommendation Based on the simulation analysis presented above, we ll recommend using RED to get satisfactory performance for both the CBR and TCP traffic. Even though this may compromise the off-peak TCP performance, the network can maintain sustainable performance during rush hours where CBR traffic challenges the capacity of the WAN. On the other hand, we d like to acknowledge the limitation of queueing optimization. To solve the bottleneck problem, sooner or later we have to consider increasing the WAN link capacities. Indeed, further simulations have revealed that the congestion issue will ease out by simply upgrading the R4-R3 link capacity to 3Mbps. 5