Access Flow Control scheme for ATM Networks using Linear Prediction
5.5 Simulation Results
5.5.4 Test 4, Heterogeneous Multiplex Scenario
Graphs 5.18, 5.19, and 5.20 show the results when a heterogeneous multiplex of 4 trace-2 and 4 trace-3 MPEG sources fed a buffer with service rate 14400 cell/second.
When compared to the CB scheme, the ALP scheme shows an improvement of 3-7 times in CLR, 0.2-0.6 in delay rate and higher utilisation. The NN scheme shows higher delay and lower CLR when compared to the ALP scheme. However, at the buffer size of 200 cells, the ALP scheme shows slightly lower delay and CLR, when compared to the ALP scheme.
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200 230 260 290 320 350
Buffer Size (cells) 1e−06
1e−05 1e−04 1e−03 1e−02
CLR
No feedback scheme CB scheme, Thr. = 0.7 ALP scheme
NN scheme
Graph 5.18 CLR Comparison, 4 Trace-2 + 4 Trace-3, Service Rate 14400 cell/sec.
200 230 260 290 320 350
Buffer Size (cells) 0.0
0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
Delay Rate
CB scheme, Thr. = 0.7 ALP scheme.
NN scheme.
Graph 5.19 Delay Comparison, 4 Trace-2 + 4 Trace-3, Service Rate 14400 cell/sec.
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200 230 260 290 320 350
Buffer Size (cells) 0.654
0.656 0.658 0.660 0.662 0.664
Server Utilisation
No feedback scheme CB scheme, Thr. = 0.7 ALP scheme
NN scheme
Graph 5.20 Utilisation Comparison, 4 Trace-2 + 4 Trace-3, Service Rate 14400
5.6 Summary
Linear traffic prediction has been used in literature in adaptive dynamic bandwidth reservation for MPEG video [ADAS96]. In this chapter, linear predictors were tested in the application of access flow control. It was found that the ALP scheme has the following advantages over the other access flow schemes.
• When tested on single, homogenous and heterogeneous multiplex of sources, the ALP scheme out-performed the CB scheme in CLR, delay and utilisation.
• The ALP scheme is an adaptive scheme that does not require knowledge of the auto-correlation of the sequence, this makes it preferable when compared to the NALP and NN schemes.
• Although “a variation of the LMS algorithm is the perceptron algorithm used in pattern recognition and is the starting point for the design of a neural network ”
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[HAYE96], the ALP scheme using the LMS approach was found to be competitive when compared to the ECPNN scheme proposed in [LIU95b].
• The ALP scheme is simpler in terms of computational requirements when compared to the NN schemes.
One important feature of the ALP scheme is that unlike the ECPNN and CB schemes, the increases in the buffer size does not have a strong effect on the CLR performance.
This is because the available buffer space appears in the numerator in equation (5.3), which is the regulator for the ALP access flow control scheme. This feature of the ALP scheme made the comparison with other schemes very difficult. To overcome this difficulty, different thresholds were selected for the CB schemes and certain buffer sizes were chosen to carry the comparison.
Because the ALP scheme is based on traffic prediction, it was important to find the predictor order that gives the lowest NSR. It was found that a linear predictor with a minimum order of 12 is required for traffic prediction under regulation and non-regulation scenarios. It was also found that the NSR for the source under non-regulation scenario is almost double when compared with the non-regulation scenario. This might be because the traffic characteristic changes under source regulation.
Previous traffic prediction techniques in [LIU95b], [CLER98] and [ADAS96] have experienced some prediction errors. In [ADAS96] when ALP used for dynamic bandwidth allocation it was stated that these errors resemble white noise and should be accommodated by using buffers. In [CLER98] these errors were accommodated by over-estimating the required bandwidth. These errors when negative (i.e. under-estimating the traffic) might cause cell losses when the ALP is used in the flow control
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application. In this research it was found that using the non-linear equation (5.5) gives better CLR and delay when compared with the linear equation (5.4) proposed in [LIU95a].
Although the ALP scheme does not have prior knowledge of the traffic characteristics when compared to the NALP scheme, it was found that it could still perform better than the CB scheme. The ALP scheme out-performs the CB scheme because the ALP is an explicit scheme, which takes into consideration the exact amount of buffer space available, the service rate and the characteristics of the traffic feeding the buffer. On the other hand, the CB scheme is a static scheme, when the buffer size is 200 cells the threshold (50% of total buffer size B) is 100 cells and when the buffer size is 350 cells the threshold (50% of B) is 175 cells. This means that in the second case, less reduction signals will be sent to the sources. Although the CB scheme tries to reduce the backward signals when the buffer size is increased, it is still not aware of the exact reduction required.
When compared to the ECPNN scheme the ALP scheme has the advantage of being based on adaptive on-line traffic prediction while the ECPNN scheme is trained off-line on cell loss ratio prediction. On the other hand the ECPNN scheme has the ability to capture non-linear relations between input (buffer size and cell arrival rate) and output (CLR).
In all the NN schemes explained in chapter 4, as well as the linear prediction schemes proposed in this chapter, only one FIFO buffer with a fixed service rate was examined.
When a switch with time priorities is considered, the feedback signal would be affected, not only by the arrival rate to the buffer to be controlled but also by the
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arrival rate in the higher priority buffers. The importance of the intelligent schemes could be more obvious in the time prioritised switch were they will judge the congestion conditions by monitoring all the buffers and not only the low priority buffer to be controlled. In the next chapter a NN scheme is proposed for controlling traffic flow in a prioritised ATM switch. The reasons for not using the ALP scheme in the time prioritised ATM switch will also be explained in the next chapter.