## 1 Introduction  
Internet of Things (IoT), which is widely used in real life and brings great convenience to people's lives, is a really hot research topic. The operation of IoT cannot be separated from the sensing and transmission of data. The wireless sensor network (WSN), as an important tool for data collection and forwarding in IoT, has a high research value [1]. The sensor nodes in WSN are small in size, easy to deploy, low in energy consumption, independent of each other, and usually deployed in the field of some specific monitoring areas. WSN is responsible for data sensing and transmission, mainly including sensor nodes and sink, sensor nodes sense the data and then transmit the data to the sink through one hop or multi-hop. WSN is widely used in the field of natural disaster prevention [2], agricultural and animal husbandry environment monitoring [3], and health monitoring because of its many advantages [4]. In practical applications, WSN has high requirements on the lifetime and reliability of sensor nodes, because WSN is usually randomly deployed in areas with harsh environments that jeopardize human safety or are difficult for humans to set foot in. When the batteries of sensor nodes are exhausted or network communication is interrupted, it will be more difficult and costly to manage and maintain the network manually, so it is necessary to design an energy-efficient and highly reliable routing protocol. Standard geographic routing is a routing protocol with low latency, few hops, and low energy consumption, which has become a hot research topic for many scholars in recent years [5]. However,this kind of routing also has the disadvantage of energy imbalance and unreliable data transmission. In the standard geographic routing protocol, the sensor nodes closer to the sink not only need to send the data they sense but are also responsible for forwarding the data sent by other nodes. In addition, it may face the problem of an infinite loop, which occurs when the sensor node is closer to the sink than its neighboring nodes, and it will result in the packets not being properly transmitted back to the sink. The network energy imbalance creates a hotspot problem, which leads to network holes causing the whole network performance to go down [6]. An effective way to solve the energy imbalance in the network is to use the mobile sink [7], mobile sink can realize the energy balance of the network by changing the hotspot nodes around it through moving periodically. However, after using the mobile sink, the nodes in the network need to keep updating the new position of the sink for proper data transmission; flooding to notify all sensor nodes is not energy-efficient. Moreover, the mobile sink may create long paths and its movement causes some nodes in the network to be farther away from it, which increases the delay. Therefore, there is a need to use an efficient mobile sink strategy so that the energy consumed for network updates as well as the transmission delay is kept at a small level. When facing the network unreliability problem, the standard geographic routing selects the nearest neighboring node to the sink as the next hop, but in the face of a multi-hop network environment, this strategy cannot guarantee that the node is able to accurately transmit data to the sink. When the data transmission link is broken or an infinite loop occurs, the sensor nodes continue to sense and transmit data, which undoubtedly consume unnecessary energy. Most importantly, traditional routing protocols and transmission schemes always work with all the randomly deployed sensor nodes, which are required to sense, send and forward data. In a large-scale sensor network, the number of nodes deployed is hundreds or thousands, and the sensor nodes have a certain sensing range, such a huge deployment of sensor nodes will lead to the repetition of a large amount of redundant data, which may lead to the emergence of multiple sensor nodes monitoring the same points [8].