# Optimal Energy Consumption Tasks Scheduling Strategy for Multi-Radio WSNs
## 5 Performance Evaluation and Analysis
### Simulation and Analysis  
To further evaluate the performances of OETS, some simulations are deployed using Matlab. Table 4 presents some key simulation parameters.  
In the simulation, 120 multi-radio nodes are uniformly deployed from (x = 0, y = 0) to (x = 100, y = 100). The data packet size is 64 bytes. Both the transmit power and idle listening power use the default. Figure 5 shows the network deployment in the beginning (Figure 5a) and the end (Figure 5b). The simulation ends if any one algorithm cannot effectively deliver data. The simulation results, including the first dead node, the network lifetime and the average latency, are shown in Figure 6a-c, respectively.  
As shown in Figure 6a, the first dead node is FIFO, then EMRSA and OETS last. Since FIFO does not consider the energy consumption factor, the energy consumption sharply increases along with the increasing of the number of tasks. Hence, the energy is rapidly exhausted and the node quickly dies. For EMRSA, which is greedy algorithm based, it merely optimizes the energy consumption of the current task. The energy consumption stably increases along with the increasing of the number of tasks. Therefore, the node stably exhausts the energy and dies. For our proposed OETS, it considers the global energy consumption to be optimal. The increase of energy consumption is relatively slow along with the number of task increases. Hence, the first node dies last.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameters** & **Value** & **Parameters** & **Value** \\ \hline Network size & 100 \(\times\) 100 m\({}^{2}\) & No. of packets (each tasks) & 6 \\ No. of nodes & 120 & Energy model & Battery \\ No. of RF transceivers (\(n\)) & 4 & Data packet size & 64 Bytes \\ Node distribution & Uniform & Transmit power & Default \\ No. of tasks & 200–1000 & Idle listening power & Default \\ \hline \hline \end{tabular}
\end{table}
Table 4: Some key simulation parameters.  
Figure 4: Energy consumption results.  
Figure 6b shows the network lifetime results of the three algorithms. For FIFO, along with the increase of the number of tasks, the increase of the number of dead nodes is explosive. Therefore, the network rapidly deteriorates and cannot deliver data. For EMRSA, the network lifetime is longer than FIFO, since the nodes naturally die. For OETS, this algorithm effectively decreases the energy consumption and prolongs the lifetime of the node. Hence, the network lifetime is longer than both FIFO and EMRSA.  
Figure 6c shows the average latency results of the three strategies. It is clearly observed that the average latency of our proposed strategy outperforms others since the algorithm can dynamically  
Figure 5: Topologies in simulations; (**a**) the beginning; (**b**) the end.  
Figure 6: Simulation Results: (**a**) First Node Died, (**b**) Network Lifetime, (**c**) Average Latency.  
allocate the packets to the current best RF transceiver. For the FIFO algorithm, the latency shapely increases with the increase of the number of tasks, because an increasing number of tasks makes most nodes quickly exhaust their energy and die. That leads to a loss of the effective data link and increases the high latency. For the EMRSA, the latency increases with the increase in the number of tasks, for reasons similar to the FIFO algorithm.