Figure 4: Average Number of Connections in Steady State.
Figure 5: Average Number of Accepted Connections (Two Destinations).
Figure 6: Average Number of Accepted Connections (Five Destinations).
In a first series of experiments, we studied the effect of the relaxation factors , i.e., the factors determining whether resources should be relaxed more at the source or at the receivers, on the performance of the algorithm. In these experiments, we keep the arrival rate constant to be 100 times the service rate. Figure 4 shows the average numbers of accepted connections for a varying value if and increasing numbers of destinations per connection. In the case of one of two destinations per connection, all connections are accepted. As to be expected, the acceptance rate decreases with increasing numbers of destinations per connection, as the connections put more load on the system.
For connections with one or two destinations, the value of has virtually no effect on the call blocking probability. This is because uneven resource allocation cancel each other out in average for these essentially unicast connections.
As the number of destinations per connection increases, the effect of varying becomes more pronounced. The results shows that the acceptance rate is higher for a relaxation factor larger than 1. In this case, more resources are relaxed at the destinations, since there are many more destinations than senders, the total amount of resources used per connections is reduced with increasing value for the relaxation factor .
We notice that very large (larger than 2.0) or very small (smaller than 0.5) values for do not significantly influence the acceptance rate. This can be explained because the relaxation factor determining the calculation of the target delay trd at the node, which gives only an indication on how much resources can be relaxed. The actual overall amount of resources freed depends on the current resource use at that node, and the remaining portion is carried forward for relaxation on the next node downstream. According to the results on these experiments, we identified a value for of 2.0 to give good resluts, and will therefore use it in the following experiments.