# Energy-Efficient Hybrid Routing Protocol for IoT Communication Systems in 5G and Beyond
## 5 Performance Evaluation and Discussion
### Energy Efficiency  
Here, the energy efficiency of the proposed MIMO-HC is analyzed. Figure 10 shows the energy cost that the cluster heads expense at MIMO-HC and UN-LEACH algorithms. The horizontal axis displays 20 sampled rounds of simulation, while the vertical axis displays the cost of energy expended by the cluster heads. The findings reveal that the energy that cluster heads consume on MIMO-HC in every round is much lower than when using UN-LEACH. Furthermore, by looking at Figure 11 the MIMO-HC equalized the depletion of energy among the cluster heads better than UN-LEACH. This happens due to cluster heads convey data in the UN-LEACH direct to the central station, and that incurs extra energy. Another factor is in the UN-LEACH method the cluster heads are not spread equally all over the network because of the random selection of the cluster heads. Figure 9: Delay. By contrast, cluster heads in MIMO-HC communicate with the central station through mixed hop (i.e., multi and single hops), and use sub-optimal routes among the cluster heads and the central station. As such, they transmit data via sub-optimal paths chosen at random which enable them to save a considerable amount of energy. Furthermore, the energy efficiency of our proposed model is investigated by evaluating the lifespan of the network (see Figure 12). Figure 12 displays the time at which the first and the final nodes die. As compared with the UN-LEACH, the MIMO-HC improves the time until both the first node and the final node die. Figure 11: Divergence of energy depletion among cluster heads. Figure 10: The amount of energy consumed by cluster heads. Figure 8 shows that the number of clusters in the MIMO-HC is steadier than in the UN-LEACH. Additionally, Figure 12 shows that the number of clusters in MIMO-HC has longer stability period than the UN-LEACH, where all the nodes in the MIMO-HC remain alive for 300 rounds and 50 rounds for the UN-LEAH. Consequently, the MIMO-HC has stable type of cluster in each round. This is due to the MIMO-HC can generate unequal clusters (using Equation (3)). In addition, using a _Th_ value can ensure that clusters closer to the central station with small radius will use multi-hop topology and clusters far away from the central station with large radius will use single-hop topology. Considering a sensing area of 200 m \(\times\) 200 m, the UN-LEACH graph shows that sensor nodes die earlier as compared to MIMO-HC due to thinly scattered sensor nodes, which consume more energy for data transfer over large distance to their own Cluster Head. In addition, Cluster Head in UN-LEACH deplete additional energy to relay the data immediately to central station over a large distance. Contrary to the existing technique, the proposed MIMO-HC overcomes these drawbacks by carrying data to the particular Cluster Head using mixed chain and single-hop schema. Moreover, nodes at a distant location from the central station with little remaining energy are not determined to be the final Cluster Head. Finally, Figure 13 depicts the number of communication rounds in an area of 200 m \(\times\) 200 m when a 1, 20, 50, and 100% of sensors perishes. Sensors at this area start to fall at a faster pace after around 20% of the sensors have perishes. This is attributed to the large range among the sensors, and each sensor node wants to be a leader head. This induces a quick energy consumption. The number of rounds in MIMO-HC is approximately 3 times more than in UN-LEACH [11], when 1, 20, 50, and 100% of sensors perishes for a zone size of 200 m by 200 m. In addition, Figure 14 displays the result of an area of 200 m \(\times\) 200 m with 300 node density (i.e., with an additional 150 nodes) when a 1, 20, 50, and 100% of sensors perish. It shows that the network in the proposed MIMO-HC is scalable and has a longer network lifetime than the network with only 150 nodes. This is, therefore, the additional nodes deployed can be regarded as increasing the total energy of the network. Figure 12: Network lifetime.