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accuracy of congestion loss.
With respect to TCP Veno, TCP Venoplus improves the accuracy of congestion loss identification, providing significant enhancement on performance.
Since the performance of the propose scheme depends on the estimation accuracy of congestion state, which is affected by the communication environments, we evaluate the proposed scheme in two kinds of scenarios: global scenario and local scenario.
At ten hops, TCP NRT achieves more than 80% accuracy in detecting random packet loss RTOs compared to EQRTO. Figure 17 shows the accuracy of congestion packet loss RTOs in terms of the number of hops.
Due to the highest accuracy of TCP NRT, it can achieve significant improvement in the performance of TCP in MWNs. Figure 16 Accuracy of random packet loss RTOs. Figure 17 Accuracy of congestion packet loss RTOs. Figure 18 Accuracy of spurious RTOs. Figure 19 Accuracy of random packet loss RTO and spurious RTOs.
We measured the accuracy of congestion loss (ACL), random loss (ARL), and packet reordering (APR) where, where NCL is the number of congestion packet loss exactly identified as congestion by TCP NCE compare to other algorithms, and NCLTotal is the number of packet loss caused by network congestion.
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It is evident that when buffer load increases upto 90%, the accuracy of non-congestion event becomes higher.
On the other hand, when the buffer load is greater than 90%, the accuracy of non-congestion event decreases.
Because when accuracy of non-congestion event increases, obviously the TCP performance also increases [22 24] compared to traditional TCPs.
We use TCP connection with 3% random packet loss and 1% packet reordering with bottleneck capacity 6 Mbps and propagation delay 10 ms. We measured the accuracy of non-congestion events (NCEaccuracy) using equation (10), (10).
Simulations through TransModeler indicate that our scheme ensures the accuracy of the estimation of congestion degree.
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