# Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks
## 5 Simulation Setup and Experimental Results
### Number of Alive Days  
Extended network lifetime has a significant role in improving the performance of the applications. In Figures 5-7, the performance of EAR is shown and compared with RNF, DPCRA, ACR, and ACRA in form of number of alive nodes. In these experiments, we used the results of three scenarios with different network topologies. In scenario-1, we used 1200 \(\times\) 1200 m\({}^{2}\) network size with number of maximum 200 nodes that include 27 actor and 173 sensor nodes. Sixty five connections are established to cover the entire scenario. Based on the results, we observed that 24 nodes have 78 alive days in our approach and same days with compared approaches, but when the number of nodes increase up to maximum 200 nodes, then the number of alive days are different. Our approach has slight edge over other competing approaches. In our approach, the nodes are alive up to 367 days as compared with other approaches that have less alive days. RNF approach has 323 alive days, and ACRA has 362 alive days. In scenario-1, our proposed EAR has improvement over other competing approaches of 1.36-11.98%. In scenario-2, we used 1000 \(\times\) 1000 m\({}^{2}\) network size with number of maximum 54 actor nodes with 15 connections. Based on the results, we observed that actors are alive for 643 days in our approach, while other approaches have actor life of 512-592 days. ACR approach has less 512 alive days, and RNF has 588 alive days. In scenario-2, our proposed EAR has improvement over other competing approaches of 7.93-20.37%. \begin{table}
\begin{tabular}{c c} \hline \hline
**Used Parameters** & **Parameters’ Description** \\ \hline
**Transmission Range** & 70 m \\
**Sensing Range of sensor node** & 35 m \\
**Initial energy of a sensor node** & 4–10 J \\
**Initial energy of an actor node** & 20–40 J \\
**Sensing Range of an actor node** & 65 m \\
**Bandwidth of sensor node** & 50 Kb/S \\
**Bandwidth of an actor node** & 4 Mb/s \\
**Simulation time** & 36 min \\
**Maximum nodes** & 400 \\
**Number of sensors** & 173–346 \\
**Static Sensor** & 80\% \\
**Mobile Sensor** & 20\% \\
**Number of actors** & 27–54 \\
**Actor-Sensor Ratio** & 13.5:86.5 \\
**Network Size** & 1000 \(\times\) 1000 m\({}^{2}\), 200 \(\times\) 1200 m\({}^{2}\), 1400 \(\times\) 1400 m\({}^{2}\) \\
**Number of hops in network** & 18 Maximum \\
**Models** & EAR, RNF, DPCRA, ACR, and ACRA \\
**Buffering capacity at sensor and actor** & 50 \& 300 Packets buffering capacity at each sensor and actor respectively \\
**Mobility (Speed of the nodes)** & 0 m/s to 12 m/s \\
**Data Packet size** & 512 bytes \\
**Initial pause time** & 20 s \\
**Rx energy** & 12.4 mW \\
**Tx energy** & 0.60 mW \\
**Power Intensity** & \(-\)14 dBm to 13 dBm. \\
**Total simulation time** & 36 min \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summarized simulation parameters for the proposed EAR. Figure 5: Number of alive nodes after completion of 12 events with 1200 \(\times\) 1200 m\({}^{2}\) network topology (Results obtained from Scenario-1). Figure 6: Number of alive nodes after completion of 12 events with 1000 \(\times\) 1000 m\({}^{2}\) network topology (Results obtained from Scenario-2). In scenario-3, we used 1400 \(\times\) 1400 m\({}^{2}\) network size with number of maximum 400 nodes that include 54 actor and 346 sensor nodes. Seventy five connections are established to cover the entire network scenario. Based on the results, we observed that nodes have lifetime 671 days in our proposed EAR approach, whereas other approaches have alive nodes 485-571 days. The performance of the network in ACRA is greatly affected which has minimum of 485 alive days. Therefore, our proposed EAR has improvement over other competing approaches of 14.9-27.71% in scenario-3. The reason of the better stability of our approach is the usage of the RSSI model that helps to determine the proper distance between sensor-to-sensor, sensor-to-actor and actor-to-actor nodes. Furthermore, the network integration message process connects the entire network.