## 2 Literature Review  
In the study in [17], the authors proposed a routing scheme called the QoS multicast-routing method based on the tuned cuckoo algorithm (TCSA). The TCSA algorithm was compared to a particle swarm optimization (PSO) to evaluate the performance of the two routing algorithms. The authors considered three quality metrics: packet-delivery ratio (PDR), path-success ratio, and the average end-to-end delay. The results show that the TCSA scheme performed better than the PSO scheme. Unfortunately, the scheme did not consider real-time applications. The TCSA scheme can be modified to consider real-time applications and the residual energy to determine the network lifetime and stability.  
In CRAHNs, the frequent connection failures and the loss of packets affect the routing performance. The mobility of nodes and overcrowding should be considered because they cause network bottleneck. In the study in [18], the authors proposed a QoS-aware routing algorithm that enhances network performance. They proposed a solid energy-efficient QoS established on congestion and delay. The development is based on using the strongest signal, queue-length drains rate, and delay. The results show that the algorithm performs better. However, throughput was not considered. Hence, the scheme can be enhanced to address the throughput metric and the PDR.  
In the study in [19], the authors proposed an algorithm known as cuckoo search ad hoc on-demand distance vector (CSAODV). The scheme was proposed to address the routing in MANET. The scheme's objective was to reduce the end-to-end delay and the number of packets lost as well as ameliorate the throughput. The CSAODV protocol is designed to select relatively stable paths. The AODV and CSAODV, in an environment where nodes are moving fast or the speed of the nodes is increasing, the performance of network is degraded. The performance of the CSAODV was superior to that of the AODV.  
The authors also noticed that in an environment with different traffic loads, the CSAODV impacts negatively on the bandwidth and delay which affects the performance of the routing protocols. The network load however, is distributed across the network. The CSAODV protocols can be enhanced to utilize the QoS requirements to make certain that a selected path has sufficient network resources and should consider the requirements of real-time applications.  
In the study in [20], the authors proposed an efficient routing scheme known as the FACE routing optimized utilizing the genetic algorithm. FACE routing uses intelligence to determine the mobile node's location. The genetic algorithm and FACE routing, which reduces the routing overhead, such as delay time and packet loss, ameliorates the network performance. The algorithm considers the QoS characteristic, which is the main objective of ensuring network availability. This ensures that while retransmission of packets takes place, the energy consumption is minimized.  
In the study in [21], the authors proposed a secure routing protocol known as trust-predicated routing (TPR), which utilizes the cuckoo search algorithm. The TPR scheme guarantees reliability, and the cuckoo search minimized the processing time and facilitated efficient routing. The results show that the proposed scheme performs better in terms of PDR, but its drawback is its poor end-to-end delay. However, its energy consumption is good. The study proposed an algorithm known as the optimized CSAODV (OCS-AODV) scheme, and it was compared to two existing schemes, namely cuckoo search-destination sequence distance vector (CS-DSDV) and ant colony optimization ad hoc on-demand distance vector (ACO-AODV) routing protocols.