Traffic Management for the Available Bit Rate (ABR) Service in ...
Traffic Management for the Available Bit Rate (ABR) Service in ... Traffic Management for the Available Bit Rate (ABR) Service in ...
depth in chapter 8. Averaging the number of sources and averaging the load factor as explained earlier in this chapter can also alleviate this problem. 6.22.9 ACR Retention ACR retention is the problem which occurs when sources are not able to fully use their rate allocations. For example, the input to the ATM end-system can be steady, but have a rate lower than its ABR allocation (allowed cell rate). Another example is an end-system which supports multiple VCs (to possibly di erent destinations) on a single outgoing link. A VC may notbe able to use its ACR allocation because the outgoing link is running at capacity. In such situations, the switches reallocate the unused capacity to the other sources which are unconstrained. However, if the ACR retaining sources suddenly use their allocations, a potential overload situation exists. Figure 6.33 illustrates the performance of ERICA when there are ten VCs sharing a link. This larger number of connections has been selected to demonstrate the scalability of ERICA to more VCs, as well as to aggravate the problem of ACR retention. Initially, the ten sources are retaining their ACRs, and each cannot send at a rate of more than 10 Mbps. After 100 ms, all the sources suddenly start sending at their full allocations. ERICA rapidly detects the overload and gives the appropriate feedback asking sources to decrease their rates. All the ten sources stabilize at their optimal rates after that. Figure 6.34 shows how the per-VC CCR measurement option can mitigate the overload situation arising when all the ACR retaining sources start transmission at their full capacities. The per-VC CCR measurement results in more conservative initial allocations, and hence smaller queues in this case. 197
6.23 Summary of the ERICA and ERICA+ Schemes This chapter has examined the ERICA and ERICA+ schemes, explicit rate in- dication schemes for congestion avoidance in ATM networks, and explained several extensions and enhancements of the scheme. The scheme entails that the switches periodically monitor their load on each link and determine a load factor, the available capacity, and the number of currently active virtual channels. This information is used to calculate a fair and e cient allocation of the available bandwidth to all con- tending sources. The algorithm exhibits a fast transient response, and achives high utilization and short delays, in addition to adapting to high variation in the capacity and demand. Based on the discussion of requirements of switch algorithms in chapter 3 we have examined how each of these requirements can be tested. Using these techniques, we presented a comprehensive performance evaluation of the ERICA switch algorithm and demonstrated the e ect of several features and options of the algorithm. We have examined the e ciency and delay requirements, the fairness of the scheme, its transient and steady state performance, its scalability, and its adaptation to variable capacityandvarious source tra c models. Simulation results have illustrated that the algorithm gives optimal allocations, and rapidly adapts to load and capacity changes. The performance of the algorithm was examined for various con gurations, source models and background tra c patterns. 198
- Page 173 and 174: have: and y 0 = y(1 ; ) z x + y 0 =
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6.23 Summary of <strong>the</strong> ERICA and ERICA+ Schemes<br />
This chapter has exam<strong>in</strong>ed <strong>the</strong> ERICA and ERICA+ schemes, explicit rate <strong>in</strong>-<br />
dication schemes <strong>for</strong> congestion avoidance <strong>in</strong> ATM networks, and expla<strong>in</strong>ed several<br />
extensions and enhancements of <strong>the</strong> scheme. The scheme entails that <strong>the</strong> switches<br />
periodically monitor <strong>the</strong>ir load on each l<strong>in</strong>k and determ<strong>in</strong>e a load factor, <strong>the</strong> available<br />
capacity, and <strong>the</strong> number of currently active virtual channels. This <strong>in</strong><strong>for</strong>mation is<br />
used to calculate a fair and e cient allocation of <strong>the</strong> available bandwidth to all con-<br />
tend<strong>in</strong>g sources. The algorithm exhibits a fast transient response, and achives high<br />
utilization and short delays, <strong>in</strong> addition to adapt<strong>in</strong>g to high variation <strong>in</strong> <strong>the</strong> capacity<br />
and demand.<br />
Based on <strong>the</strong> discussion of requirements of switch algorithms <strong>in</strong> chapter 3 we have<br />
exam<strong>in</strong>ed how each of <strong>the</strong>se requirements can be tested. Us<strong>in</strong>g <strong>the</strong>se techniques, we<br />
presented a comprehensive per<strong>for</strong>mance evaluation of <strong>the</strong> ERICA switch algorithm<br />
and demonstrated <strong>the</strong> e ect of several features and options of <strong>the</strong> algorithm. We<br />
have exam<strong>in</strong>ed <strong>the</strong> e ciency and delay requirements, <strong>the</strong> fairness of <strong>the</strong> scheme, its<br />
transient and steady state per<strong>for</strong>mance, its scalability, and its adaptation to variable<br />
capacityandvarious source tra c models. Simulation results have illustrated that <strong>the</strong><br />
algorithm gives optimal allocations, and rapidly adapts to load and capacity changes.<br />
The per<strong>for</strong>mance of <strong>the</strong> algorithm was exam<strong>in</strong>ed <strong>for</strong> various con gurations, source<br />
models and background tra c patterns.<br />
198