## 1 Introduction  
WSN-assisted IOT is used for data collection in the environment and detect the certain events of significance in the physical world. It can bring great convenience to people's life [1; 2; 3; 4], such as environmental monitoring, military tracking, and health observations. Sensor nodes send the sensed information to the base station (BS) by single hop or multi-hops. Therefore, the energy consumption and location deployment of the nodes can affect the network lifetime. The sensor nodes are generally powered by battery, which can only maintain a limited lifetime because of the limited energy, and the cost of replacing the battery is relatively expensive and hard to achieve. Numerous researches have shown that the energy consumption of nodes in WSNs is mainly in data transmission during routing [5]. Therefore, how to design energy balanced and efficient routing algorithms to prolong network lifetime is the key to the development of WSN-assisted IOT.  
There are a lot of existing routing protocols to extend the network lifetime, which are mainly divided into three aspects: (1) minimize the path energy consumption. Minimizing the path energy consumption is to save the energy of the entire network by adopting the shortest routing path or reducing path relay hops [6]. (2) Balance the energy between nodes. This method tries to consume the energy of the nodes in the network as evenly as possible, thereby delaying the death of the first node and extending the network lifetime. (3) Transmission power control. To reduce energy consumption of data transmission, the methods of transmission power control measure and model RSS (received signal strength) to obtain optimal data transmission power, which is used to decrease channel interference among sensor nodes [7; 8; 9]. However, once the path failure happens, the related nodes need to re-establish the network topology [10].  
Based on the above observations, in order to balance and efficiently utilize energy to extend the network lifetime, we propose an energy-balanced routing algorithm for network lifetime enhancement (EBRA-NLE) based on DS evidence theory [11]. DS evidence theory can fuse multiple attributes according to DS fusion rules and make the optimal choice, so it is applied to our routing selection for WSNs. Our main contributions are summarized as follows:  
* In WSN, many previous researches on DS evidence theory mainly focus on data fusion to enhance the reliability and security of information acquisition, but the application of indexes fusion in sensor nodes as a routing decision-making method is very few. In this paper, we adopt DS fusion rules to fuse three attribute indexes that affecting energy balance and energy efficiency of each node.
* First, the node's forward neighboring nodes are taken as the evaluation object, and three indexes are established as evaluation objects from the perspective of energy balance, minimization of path energy consumption, and buffer proportion. It should be noted that, in order to reflect the importance of each index according to the difference in attributes between nodes, a sine function is adopted to map the belief function corresponding to each index. Then DS fusion rule is utilized to comprehensively evaluate the indexes of each node to obtain the optimal path selection.
* Simulation results show that the proposed EBRA-NLE has certain advantages in prolonging network lifetime and balancing energy between nodes. In addition, the network lifetime obtained by EBRA-NLE is improved about 313% and 72% more than that of MCRP and DS-EERA algorithm respectively.  
The rest of the paper is organized as follows: Section 2 reviews the related research works. The system model is introduced in Section 3. The EBRA-NLE algorithm is presented in detail in Section 4. The relevant simulation results are analyzed and discussed in Section 5. Finally, the conclusion is summarized in Section 6.