## 4 Evaluation
### Testbed Results of Protocol Performance  
In this section, we study the protocol performance of opportunistic routing (CAOR [15]) and flooding (CoCo [17]) with LACE.  
Figure 5 shows the delay comparison of LACE-CAOR and the original CAOR with BCM. The delay here denotes the time from the transmission of a packet to the reception of the packet at the destination node. We can see that LACE-CAOR's routing delay is less than CAOR. Though the same routing strategies are used in CAOR and LACE-CAOR, the measured/estimated link correlation is different. With a more accurate estimation, LACE-CAOR is able to find network neighborhoods with much spatial diversity, while CAOR's routing decisions actually find neighborhoods with less spatial diversity. More specifically, the performance improvement is larger in Channel 16 than in Channel 26. The reason is that Channel 16 is has more severe interference from WiFi traffic and has a stronger link correlation than Channel 26. There are inherently fewer neighborhoods with a weak link correlation in Channel 16 than in Channel 26. As a result, the identification of weak link correlation areas can contribute more to the end-to-end delay performance in Channel 16. On the other hand, most neighborhoods in Channel 26 have weak link correlations, and the BCM-based method can also find a weak link correlation neighborhood. The performance improvement then becomes less.  
Figure 5: Delay performance evaluation with CAOR [15].  
Figures 6 and 7 evaluate the performance of CoCo and LACE-CoCo. Figure 6 shows the measurement/estimation accuracy of LACE and BCM. We can see that: (1) as expected, LACE is more accurate than BCM; and (2) the accuracy difference is much larger than that in Figure 4b. The reason is that LACE-CoCo aims to disseminate multiple packets, which increases the number of samples for calculating long-term link correlation (while in CAOR, only one packet is transmitted at a time). Since there are more historical traces, the \(ch\) part can be estimated more accurately. On the other hand, BCM performs similar under different data trace situations.  
Figure 7 shows the protocol performance of CoCo and LACE-CoCo. We can see that: (1) LACE-CoCo greatly outperforms CoCo; (2) the improvement is much larger than the improvement in CAOR. The reason is that link correlation in the scenario of multi-message flooding is estimated more accurately. Thus, the desired link correlation can be more accurately identified. Since there are multiple packets to transmit, the \(\alpha\) is tuned large, containing a more long-term result, which is more  
Figure 6: Estimation accuracy with CoCo [20].  
Figure 7: Performance evaluation with CoCo [20].  
stable than the short-term result and is more error-tolerate. (3) The improvements in both channels are similar. The reason is that in CoCo, all network nodes should eventually receive the broadcast packets. Thus, all network neighborhoods can be effective during the transmission progress, and there are more useful routing decisions. While in CAOR, only the nodes on a certain path are used, and there is more performance variation in OR than in multi-message flooding.