## 5 Evaluation
Accordingly, in topology 1 for example, the success probability of link \((2,d)\) increases from 60.4% to 66.7% for \(\gamma\) = 0.5, when SIC is employed at \(d\), instead of IAN. This increase in the success probability is significantly lower than the corresponding one for link \((1,R)\). The reason for this is the different asymmetry between interfering links for the two receivers. As Figure 2 also shows, the distance of interfering node 2 from \(R\) is much smaller than the distance between 1 and \(R\). The distances, however, of nodes 2 and \(R\), from \(d\), are very similar. A notable effect of combining SIC with the TOFRA flow allocation scheme is the utilization of paths that were assigned zero flow when IAN was applied at receiving nodes. As Tables 3-5 show, the utilization of path \(1\to R\to d\) becomes non-zero for all topologies and \(\gamma\) values considered when SIC is employed. In the third part of the evaluation process, the proposed scheme is compared with FMP and best path-based flow allocation schemes, both in terms of throughput and delay. Variants of the TOFRA scheme achieve higher AAT than the corresponding full multipath (FMP) variants, for all topologies and \(\gamma\) values employed. The main reason for this is that FMP assigns one packet per slot on each path in an interference unaware manner, resulting in a higher fraction of data packets retransmitted due to interference. This performance gap becomes even more profound when large SINR threshold values are assumed where the success probability of all links is decreased. Considering topology 3, with \(\gamma\) = 0.5 for example, TOFRA-SIC\((R,d)\) achieves 10.2% higher AAT than the corresponding FMP variant (FMP-SIC\((R,d)\)). Compared to BP\({}_{c2e}\), TOFRA-IAN achieves the same AAT, for almost all scenarios explored, since they both utilize at full rate path \(2\to d\). The only exception to this is the scenario based on topology 3, where \(\gamma\) = 0.5. In this scenario, the corresponding TOFRA variant also utilizes path \(1\to R\to d\). When TOFRA, however, is combined with SIC, at both \(R\) and \(d\) and a low \(\gamma\) is employed, it achieves higher AAT. In topology 3 for example, when a \(\gamma\) value equal to 0.5 is employed, TOFRA-SIC\((R,d)\) achieves 15.4% higher AAT than BP\({}_{c2e}\). It should be noted, however, that the prospect of higher throughput for TOFRA is limited by the number of paths available. In [24,26] where several paths are employed in parallel, TOFRA outperforms the corresponding best-path variant. Finally, the best-path variant, which selects the path with the widest bottleneck link, in terms of success probability (BP\({}_{wb}\)), utilizes path \(1\to R\to d\) for topologies 1 and 2, and \(2\to d\) for topology 3. However, as Tables 3-5 show, TOFRA assigns zero flow on path \(1\to R\to d\) for most scenarios explored, when interference is treated as noise. This shows that utilizing this path in parallel with \(2\to d\) would result in lower AAT. As also shown in Figures 3-5, BP\({}_{wb}\) achieves the lowest AAT among all schemes, for topologies 1 and 2, and performs the same with BP\({}_{e2e}\) for topology 3. To summarize, simulation results presented in Figures 3-5 reveal that TOFRA, when combined with SIC at both the relay and the destination, achieves the highest AAT than all flow allocation schemes in almost all topologies and \(\gamma\) values considered. The only exception is the simulation scenarios derived from Topology 1 and \(\gamma\) values 1.5 and 2.0. In these scenarios, the variant of TOFRA that treats interference as noise achieves the highest AAT along with \(BP_{e2e}\). In this part of this section, the aforementioned flow allocation schemes are also compared in terms of delay. More precisely, the average flow delay, measured in slots, for each scheme is estimated.