# Context-Aware Gossip-Based Protocol for Internet of Things Applications
## 6 Effects on Application Requirements
### Critical IoT Applications  
Time-critical IoT applications require an ultra-low end-to-end delay to ensure that messages are received as soon as possible. In the motivating scenario (see Section 3), if [PERSON]'s motion fails to be captured by the motion sensors, [PERSON] (the domiciliary carer) will need to be notified immediately so that she can change her usual route to reach [PERSON] quickly or notify an ambulance. Based on the results described in Section 5 and summarised in Table 4, to ensure a reduced end-to-end delay for immediate response, the following parameters need to be activated:  
* Sink distance (\(f3\)): this parameter linearly impacted the performance of the end-to-end as the number of nodes in the network increases. This is demonstrated in Figure 2, where the end-to-end delay for the sink distance parameter proved the lowest of the other five parameters. Therefore, the sink distance (\(f3\)) is highly suitable for consideration in critical IoT applications.
* Node density (\(f4\)): the number of neighbours is important to ensure successful message delivery. For instance, if a node has no neighbours, then it cannot rebroadcast a message, and hence, the sink node will not receive it. Therefore, the more neighbours there are, the higher the rebroadcast and delivery probabilities.
* Message priority (\(f5\)): the message priority parameter is activated, and a critical message is classified as high priority to ensure its rapid delivery. The impact of this parameter was confirmed in Section 5, where the performance of the message priority parameter was the second lowest (after sink distance) as shown in Figure 2.  
While the residual energy (\(f1\)) when observed in isolation produced low end-to-end delay (see Figure 2), the critical message should be sent to the node that is closest to the sink event if was  
\begin{table}
\begin{tabular}{l c c c} \hline \hline \multirow{2}{*}{**Weighted Parameter**} & \multicolumn{4}{c}{**IoT Application**} \\  & **Critical** & **Energy-Efficient** & **Bandwidth-Intensive** \\ \hline (\(f1\)) Residual energy & & \(\times\) & \(\times\) \\ (\(f2\)) Next-node distance & & \(\times\) & \(\times\) \\ (\(f3\)) Sink distance & \(\times\) & & \(\times\) \\ (\(f4\)) Node density & \(\times\) & & \(\times\) \\ (\(f5\)) Message priority & \(\times\) & & \(\times\) \\ \hline
**Evaluation Metric** & & & \\ \hline End-to-end delay & \(\downarrow\) & \(-\) & \(-\) \\ Rebroadcast nodes & \(-\) & \(-\) & \(\downarrow\) \\ Saved rebroadcasts & \(-\) & \(-\) & \(\uparrow\) \\ Network lifetime & \(-\) & \(\uparrow\) & \(-\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Manipulated parameters for critical, bandwidth-intensive, and energy-efficient applications based on the previous simulation results (see Section 5). The desired impacts on the evaluation metrics for each class of IoT applications considered in this paper are also shown. \(\uparrow\), \(-\), and \(\downarrow\) indicate desired increased, average, and reduced impacts, respectively, on an evaluation metric.  
short on energy. Therefore, the adapted MFWF for critical IoT applications is formulated according to Equation (10):  
\[w=f_{3}\cdot p_{3}+f_{4}\cdot p_{4}+f_{5}\cdot p_{5} \tag{10}\]  
where \(p_{3}\) is defined in Equation (6), \(p_{4}\) is defined in Equation (7), and \(p_{5}\) is set to 1 for high-priority messages.