## 2 Related Work  
Many researchers have paid attention to how to reduce energy dissipation for IoT devices due to limited energy resources by the battery [26]. [PERSON] et al. [27] have proposed efficient energy based on the clustering routing technique for resource management (EECBRM) in an IoT environment. Firstly, EECBRM employs the fuzzy logic method to group IoT devices (sensor nodes) in the network into clusters. Then, the optimal lion whale algorithm with tumbling (LWOT) is used to discover the optimal paths from IoT devices to the sink. [PERSON] and [PERSON] [28] have proposed an energy efficiency optimal multi-path routing protocol to improve QoS in WSN for IoT applications (EOMR), in which the authors constructed multiple paths based on the estimated optimal factors with the measure of the lifespan of a node, reliability of communication, and traffic intensity. The authors in [29] have proposed an application-centric information-aware routing technique for the IoT platforms assisted by WSNs (ACIAR) by integrating WSN with IoT to find routes and process information for requested IoT applications. [PERSON] and [PERSON] [30] introduced a scalable and energy-efficient routing protocol (SEEP) in which the total network area is divided into some sub-areas (clusters), and each cluster elects a cluster head (CH), a relay node (RN), and member nodes. RNs receive collected data packets from MNs and data fusion and send it to the CH. CHs are responsible for forwarding their fused data packet to another CH or the base station (BS). [PERSON] et al. [31] proposed a dynamic clustering approach based on a genetic algorithm for WSN-based IoT applications. According to this proposal, the authors have established dynamic clustering in WSN by using parameters such as direct distance among nodes and the BS, communication energy cost, and the number of transmissions for the fitness function of heredity to decrease energy consumption. [PERSON] et al. [32] presented a cluster tree-based energy-efficient routing protocol (CTEER) in WSNs. CTEER constructs a robust routing tree with a centered sink in which all sensor nodes can only communicate with their parent on the branches in the direction of the mobile sink in order to avoid lots of energy dissipation generated by long-distance communication. Therefore, it improves network efficiency. [PERSON] et al. [33] proposed an energy-efficient-adaptive clustering formation mechanism for WSN (ECFE) in which the CHs are chosen based on the value of energy efficiency welfare (EEW). EEW contains the residual energy of sensor nodes and the Euclidean distance among them in the same cluster. ECFE achieves energy-efficiency based on dividing the nodes into a grid topology. However, the data transmission between intra-grid and inter-grid nodes and the sink is the cause of much energy consumption in IoT applications. [PERSON] et al. [34] proposed an energy-efficient distributed cluster-tree-based routing protocol for application IoT-based WSN, in which the clustering is completely distributed through exchanging messages at sensor nodes such as the LEACH protocol. The advantage of EE-DTC is that it combines the residual energy, the position, and the density of nodes as prime parameters for CH selection. Furthermore, EE-DTC discovers multi-hop routes for data transmission intra-clusters by building several MSTs to avoid communication over long links, thereby improving energy efficiency. However, distributed clustering increases extra energy consumption due to generating many messages overhead and increases workload at the CHs node due to constructing MSTs. Furthermore, using the single-hop communication method inter-cluster from CHNs towards the sink leads to high energy consumption.