Our numerical results enabled us to validate our analytical model and to quantify the gains obtained by such a joint HM and adaptive relaying scheme, in terms of mean transfer time and blocking rate, as compared to the classical relaying scheme.
The same result holds for the blocking rate also, as shown in Figure 17 for the same reasons as detailed above for the case of HM-based relaying over the classical scheme.
This is demonstrated also in Fig. 10, where the blocking rate for uncoordinated nodes is shown as a function of ρ: as expected, BR increases with ρ.
In particular, we compare the performances of our approach shown in Figure 11a with that shown in Figure 13a here (both in which the ratio of handoff arrivals to new-connection arrivals is 1 1), and it is observed that the later provides a great improvement over the former (as the blocking rate is decreased by 46.10% in average).
Inter-RAT handover performance is usually evaluated with some recognized metrics, such as drop rate, blocking rate, handover delay, and packet loss.
Then, the minimum and maximum thresholds of network loads ( n l th min, n l th max ) in Equation (2) for rtPS, ertPS, and nrtPS can be derived, respectively, depending on the currently estimated system capacity B. The performances are indexed as the connection blocking rate and the achieved QoS in terms of per-flow throughput, i.e., the average data rates supported per established connection.
Performance evaluation results obtained using simulation analysis show that the proposed re-authentication protocol enhances handover parameters such as handover latency, handover blocking rate and packet loss rate.
But as ad blocking rates continue to rise, we may finally see that begin to change.
The performance metrics are indexed as the new connection blocking rates and handoff dropping rates.
The blocking performance is used as a trigger to find new optimal allocations when blocking rates become unacceptable due to change in user demands.
