## 2 Literature Survey
This algorithm combines swarm intelligence and local search manner. With the routing protocol generated, the trajectories were obtained. The proposed algorithm was compared to the existing greedy approach and particle swarm optimization (PSO) models. In one study [26], the authors presented an energy efficient clustering and routing algorithm with artificial bee colony and metaheuristic approach. They proposed a multi-purpose fitness function using the linear programming formulation for CH selection. As for the routing problem, the transmission path is solved by the cost-based function that is calculated between the number of hops and the energy efficiency. The data in the network is collected in a distributed manner. In this study, routing discovery is designed in a very complex way. At the same way, it can be said that the node and packet load occur because the algorithm is not built on network mobility. The paper [47] compared the sleep-aware energy efficient protocol named SEED with both the homogeneous and heterogeneous models belong to wireless sensor networks. This algorithm consists of several steps, including setup and CH selection processes. It can be said that these steps do not guarantee the energy balance and consider the packet delivery rate. In one study [5], CH selection is performed according to its energy level and to the remaining energy. The sensor node with the minimum time delay comparing to others is selected as CH. In one study [37], the authors proposed a clustering algorithm called EPMS, which was used for WSNs based on the particle swarm optimization-based mobile sink node. In this algorithm, CH selection was performed based on the remaining energy and location of the node. In the routing mechanism, the virtual clustering and mobile sink techniques are combined. The network area was divided into several regions and MS collected the data by visiting CHs. The disadvantages and shortcomings of this study can be listed, as follows. In CH selection, only the remaining energy and position of the node were observed. Node degree, load energy capacity, and fitness value criteria have not been evaluated. The WSN structure is homogeneous. In real life, heterogeneous network models are important. In the energy model, only the energy consumed for transmission and reception is considered. In one study, the authors [38] presented a novel unequal clustering and routing algorithm (nCRO-UCRA) that is based on a chemical reaction to address the hot spot problem. The number of elements of the clusters close to the sink node is designed as more than other papers. CH selection was made according to the proposed cost function. As for the routing protocol, it is designed for the chemical and potential energy formulations. However, it can be said that CHs carry data into the sink node with the multi-hop method, increasing energy consumption and the possible packet delay. In one study, authors [31] proposed a bio-inspired decrete firefly algorithm (BI-DFAMDT) with the mobile data transporter (MDT) being represented by the mobile sink node. The trajectory length that was traveled by MDT was kept to a minimum with the nature-inspired metaheuristic approach. The travel time of MDT is minimized in data collection. However, we can say that MDT increases data delivery latency while gathering data from the all nodes as travelling in a non-cluster network. A study [48] proposed a routing algorithm that constructs trajectories by MS in order to reduce the energy consumption and delay that are caused by the mobile sink node. In this sense, trajectory models have been designed with different transmission paths with the reduced delay path (RDP) algorithm. MS collect data from specific nodes using these trajectories. In a study [49], the authors address the joint multi-purpose mitigatation problem by presenting both the clustering and routing problems with link quality base. They introduce a novel individual encoding scheme. Also, the energy consumption model is experienced under the real CC2420 energy radio.