## 5 Case Studies on the OMF-Enabled Testbed
### Case Study 2: Available Bandwidth Estimations
Thus, upon the end of the experiment, the avail-bw is measured in two different ways. Firstly, two independent estimates are given by pathload and spruce actively, and another estimate is given by MRTG passively. Finally, a comparative evaluation of the estimates can be undertaken to assess the accuracy of the tested active tools. However, MRTG data provides low-resolution measurements and enables us to calculate the average avail-bw every 5 min. To comply with this low resolution, pathload and spruce are executed repeatedly, and the 18 measurements are smoothed by taking the average estimates of the tools over similar 5 min periods. The D-TTG tool, which simulates the real-world cross-traffic conditions during the experiments, was also integrated into the experiment description file. In our experiments, two pairs of D-TTG senders and receivers were started on CT-S1/CT-R1 and CT-S2/CT-R2 research nodes to simulate hop-persistent cross-traffic scenarios. Particularly, the two paths between CT-S1/CT-R1 and CT-S2/CT-R2 crossing the measurement path were loaded with poissonian and exponential cross-traffic, respectively, with varying rates from 10 to 90 Mbps. The measurement path has been monitored over a period of one hour. Figure 5a illustrates the results achieved by pathload, spruce and MRTG. As pathload only gives the lower and upper bound estimates for avail-bw, the average of these two values was calculated to obtain the final estimate. The main observation is that pathload was consistently inaccurate, over-, or underestimating the avail-bw. Particularly, compared to the reference avail-bw measurements obtained by MRTG, the underestimation error of pathload ranges from 6.64% to 59.25%, whereas the overestimation error varies between 3.10% and 31.60%. In our previous study [31], we showed that the estimation results of pathload, in general, was accurate when during the measurement cross-traffic with constant rates was available on the path. These experiments, however, indicate that if cross-traffic with rapidly varying rates passes the measurement path, the tool is not able to capture the avail-bw with sufficient accuracy. In contrast to pathload, spruce was able to relatively closely track the avail-bw and correctly respond to injected cross-traffic variations. More  
specifically, compared to the reference avail-bw measurements obtained by MRTG, the underestimation error of spruce ranges from 1.53% to 10.90%, whereas the overestimation error varies between 3.28% and 12.89%. Another experiment scenario for evaluating the estimation accuracies of wbest and patchirp has been specified in a separate experiment description file using the testbed setup and configuration illustrated in Figure 2(c). As distinct from the two previous experiments, this scenario includes a mixed combination of wireless and wired links, which pose additional challenges to avail-bw estimation techniques. The main difficulty in performing avail-bw measurements over wireless links is the existence of a shared medium. Particularly, wireless nodes communicating over a shared medium can face several issues such as collisions and packet losses, which normally do not occur in wired networks. Using the ethtool, the WiFi mode of the wireless link has been set to 802.11 g. The sender and receiver components of wbest and pathchirp were run on research nodes S and R, respectively. The D-ITG sender and receiver components, on the other hand, were started on research nodes CT-S1 and CT-R1, respectively, to simulate the real-world condition of constant cross-traffic. In total, four different cross-traffic scenarios were created to investigate their effects on wbest's and pathchirp's avail-bw estimates. Particularly, wbest and pathchirp measurements were conducted when the shared medium is (a) free of cross-traffic, (b) lowly congested (i.e., appr. 3 Mbps), (c) moderately congested (i.e., appr. 6 Mbps), and, finally, (d) heavily congested (i.e., appr. 9 Mbps). Each experiment was repeated 20 times and average accuracies were then calculated.