###### Abstract
This is because the CHNs have to process many tasks and transmit data over long ranges. Thus, they exhaust quickly. The principal advantage of the clustering technique is that nodes reduce the communication routing overhead, decrease the amount of data transmitted to the sink device, and nodes go into sleep mode after finishing data transmitting. Therefore, they reduce energy consumption. However, this technique also faces many challenges, such as (1) what are the criteria for selecting CHNs that significantly have an effect on the  
Figure 1: A scenario of deploying a WSN-based IoT application. network performance; (2) how long does it take to transfer the role of CHN to another node; (3) how to choose an optimal number of CHNs, which is also an NP-hard problem because choosing \(k\) CHNs out of \(N\) nodes will give \(N/k\) possibilities [24]; and (4) MNs consume a lot of energy in transmitting direct data to their CHN because the coverage area of clusters is still large. In addition, CHNs also employ single-hop communication methods to the sink device; hence, the amount of consumptive energy used in transmitting data from CHNs to the sink will also be greater. Hitherto, many researchers suggest improving energy efficiency and prolonging the NL of WSN-based IoT applications. Typically, [PERSON] et al. [25] proposed power efficient grid-chain routing protocol (PEGCP) to lower the energy required in data transmission by dividing the whole network zone into the virtual grid (containing cells) and using chain construction methods in intra-cluster and in inter-cluster communication in which the data is only transmitted in short-links multi-hop. The simulation shows that the performance of PEGCP is much better than LEACH in the proportion of energy efficiency and NL. However, in the CHN election phase, the PEGCP had not considered the distance between the candidate CHNs and the sink, so the chosen CHNs may be far from the sink device. In addition, fixed equal cell division of the same size is not guaranteed to balance the number of nodes in each cell. These issues can be the reason for unbalanced energy consumption among sensor nodes. Therefore, in this paper, we propose an energy-efficient routing protocol based on grid-based WSN-based IoT applications (EEGT for short) in order to improve energy efficiency and extend the NL. The principal contributions of the proposed approach are as follows:  
1. We divide the whole monitored network region into the virtual grid with different cells (clusters) in order to guarantee a balanced number of live nodes jointly in each cell. 2. We select CHN in each cell by considering the combination of the residual energy and the distance from the candidate CHN to the sink device. 3. We combine tree and chain routing mechanisms for discovering data transmission routes from CMs to CHN and CHNs to the sink device by using the Kruskal algorithm and the ant colony algorithm to avoid the huge energy consumption made by the long distance between sensor nodes and the sink device. 4. In particular, we simulate the LEACH-C, PEGASIS, PEGCP, and EEGT routing protocols in many different scenarios. The simulation results in evidence that the network performance in terms of energy efficiency and the NL using our proposed protocol can be improved by 30%, 20%, and 10% compared with LEACH-C, PEGASIS, and PEGCP, respectively. The remaining structure of this paper is organized as follows: Some previous related works are reviewed in Section 2. Section 3 presents the system models, and Section 4 describes the details of EEGT. In Section 5, the evaluation and analysis of simulation results are presented. Finally, Section 6 presents our conclusion.