# Opportunistic Sensor Data Collection with Bluetooth Low Energy
## 5 Evaluation
### Maximum Amount of Collected Data per Contact Interval  
By applying Equations (6) and (23), we next compute the theoretical maximum amount of sensor data that can be collected within a contact interval, for both advertisement- and connection-based approaches. Results are shown in Figure 18, as a function of _advInterval_ and \(T_{contact}\), and assuming error-free communication, while impact of non-zero BER is evaluated in Figure 19. Note that the amount of collected data is independent of \(N\) in the advertisement-based mode (because the same advertising packet is sent through the \(N\) advertising channels used), and is negligibly affected by \(N\) in the connection-based mode. As shown in Figure 18, for low _advInterval_ values, the amount of data that can be collected from the sensor node in the advertisement-based approach is 2-3 orders of magnitude lower than that of  
Figure 19: Maximum amount of collected data per contact interval, for the advertisement-based and connection-based approaches, as a function of _advInterval_, for different BER values, and for \(T_{contact}=150\) s. _contInterval_\(=4\) s has been assumed. Figure 18: Maximum amount of collected data per contact interval, for the advertisement-based and connection-based approaches, as a function of _advInterval_, and for different \(T_{contact}\) values. Only curves for _contInterval_\(=4\) s are shown, for the sake of figure clarity. the connection-based approach. For high _advInterval_ values, the difference increases to 4-5 orders of magnitude. In the connection-based mode, the amount of sensor node data that can be collected is almost independent of _advInterval_. With the considered assumptions, if the amount of data to be collected during the contact is below 334 kbit (i.e., -42 kB), the advertisement-based approach suffices. However, for amounts of data greater than this value, the connection-based approach is the only feasible option, offering a capacity of 10 to 100 Mbit, depending on the contact duration. Considering Figures 17 and 18, a trade-off can be observed between sensor node lifetime and amount of collected data that depends on the _advInterval_ setting. For the connection-based approach, influence of _advInterval_ on the amount of collected data is low, and it decreases as \(T_{contact}\) increases because a greater part of the contact time can be used for data exchange. Increasing _connInterval_ slightly improves the amount of collected data. However, in Figure 18, only curves for _connInterval_ = 4 s are shown, for the sake of figure clarity. Figure 19 presents results on the impact of non-zero BER on the amount of data collected. As expected, this performance parameter decreases with BER. However, such decrease with BER is greater for the connection-based approach than in the advertisement-based one. In the former, when errors lead to connection event termination, relatively long periods of inactivity (between connection event termination and start of the next connection event) will reduce significantly the amount of collected data. This effect is emphasized for high _connInterval_, where the duration of inactive periods will also be high. In the advertisement-based approach, amount of collected data is only significantly affected by channel errors for BER greater than \(10^{-4}\). We have evaluated BER = \(10^{-3}\), BER = \(10^{-4}\), and BER = \(10^{-5}\), in addition to BER = 0, but only the first one leads to visible differences when compared with BER = 0 in Figure 19.  
We next provide insight on the influence of _connInterval_ on the theoretical maximum amount of data collected in the connection-based approach, for BER = 0 and for non-zero values of BER (see Figures 20 and 21, respectively). As shown in Figure 20, for a \(T_{contact}\) of 150 s and 45 s, the amount of collected data tends to grow asymptotically with _connInterval_, since a greater number of round trip exchanges are possible, and the unused part of _connInterval_ becomes smaller in relative terms.