# An Energy-Efficient Fail Recovery Routing in TDMA MAC Protocol-Based Wireless Sensor Network
## 5 Results and Discussion
### Energy Efficiency of NE-MCR  
To evaluate the energy efficiency of the proposed algorithm, we compare the network lifetime and energy consumption of NE-MCR with DCFR and ESCFR methods. In this experiment, we assume that the only cause of node failure is a dead battery for the sake of focus on the energy efficiency. For each example network, the simulation initiates the network operation by filling every node with full battery energy. As each node starts forwarding the aggregated data towards the base station, it gradually drains its battery using the energy model of Equation (6). Table 1 summarizes the unit energy parameters used by the energy model [11]. The proposed method is a route recovery method, not a node recovery. Thus, the FDT of the network is not relevant to our performance evaluation. On the other hand, the ADT is a suitable performance metric. Figure 12a compares the ADT performance of all three fault recovery routing methods, NE-MCR, DCFR and ESCFR, for the 10 network examples of Figure 11a. NE-MCR and ESCFR methods show that the ADT decreases when the number of nodes increases. Surprisingly, DCFR experiences an increase when the number of nodes grows from 400 to 500. This algorithm uses a different cost function than ESCFR and it periodically updates information regarding the available energy of all neighbor nodes. Therefore, it balances a network load more effectively than ESCFR by changing the set of nodes in backbones. In terms of NE-MCR, as the number of child nodes increases, the backup parent nodes receive more data from their child nodes and consume higher energy. Nevertheless, it still performs better ADT, since it also balances the network load considering transmission power and NBP's receiving energy during the recovery procedure. Due to the random injection of a fault, some nodes may not find closer neighbor nodes to choose as an NBP, and thus this drains their battery faster. Those nodes, therefore, may spend more transmit energy since the distance between \(MCR\_BP_{i}\) and optimal \(NBP_{i}\) is greater than others. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline \(\mathrm{E_{elec}}\) & 50 (nJ/bit) \\ \(\mathrm{E_{Fs}}\) & 10 (pJ/bit/m\({}^{2}\)) \\ \(\mathrm{E_{amp}}\) & 0.0013 (pJ/bit/m\({}^{4}\)) \\ Initial energy & 0.5 (0) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Default value of all network parameters used in the simulation. Figure 12a shows that until the number of network nodes reaches 400 (red dashed line), the ADT of NE-MCR is substantially greater than the ADT of the other two algorithms. Because, until this point, the network density is low and the nodes using DCFR or ESCFR are more likely to choose a father node that has more available energy to forward their data. As the number of nodes increases, a difference of ADT between these methods shrinks. However, we can observe that for a lower density network cases, NE-MCR algorithm improves ADT by 21% on average over the compared methods. Figure 12b compares the average energy consumption per node for all fail recovery routing methods. The average energy consumption per node grows gradually as the network density increases, and so more data is aggregated in each node. For the network of 200 nodes, our proposed NE-MCR algorithm consumes around 40% less energy than the other two reference algorithms. However, for higher density networks, NE-MCR algorithm's energy consumption grows rapidly and a difference in performance of the proposed method with DCFR shrinks up to 16% (for the network with 500 nodes). We can see some non-linearity in the performance of DCFR whereas ESCFR experiences a linear increase as the network density grows. Figure 12c compares the average energy consumption per node measured with various wireless ranges for each node. While all three algorithms have increasing energy consumption as the wireless range grows, NE-MCR shows substantially lower energy consumption in all wireless ranges tested.