## 1 Introduction  
The Internet of Things (IoT) connects a range of physical devices through a variety of transmission technologies, e.g., WiFi, 5G, wireless sensing networks, etc. IoT has become an important network infrastructure in the world of the future [1, 2, 3]. The resilience, reliability, and efficiency of agriculture and smart city services can be effectively enhanced by IoT technologies [4]. Among these communication technologies applied in the IoT networks, wireless sensor networks (WSNs) play an important role [5]. The wireless sensor network is generally composed of sensor nodes equipped with wireless communications equipment. These nodes are autonomous and spatially distributed. These nodes in operation can realize real-time monitoring of the physical environment, provide massive data for back-end services to analyze, and build an intelligent model of the sensing layer. However, the typical features of these nodes generally are limited storage, power, and computing resources. Since the purpose of WSNs is to perceive and transmit information efficiently, how to design the appropriate routing strategy will directly affect the performance of the network. Therefore, the core goal of the WSN routing strategy is to reduce energy consumption, enhance network damage resistance, and prolong network life. The routing strategy of WSNs has attracted the attention of many researchers and institutions. The Ad hoc On-Demand Distance Vector Routing (AODV) was designed for mobile ad-hoc networks [6]. The behavior of the AODV routing protocol in situations of link failures was investigated. The Destination Sequence Distance Vector Routing (DSDV) was designed to attempt to cope with the geographic mobility of network nodes [7]. The Dynamic Source Routing (DSR) was defined by [8]. The data sender can determine precisely the needed sequence of the nodes to propagate the packet. However, DSR has the disadvantage of high signaling overheads. Besides, it has been found that these routing protocols have poor performance under changing network topologies, which is very common in WSNs due to factors such as node sleeping [9]. The flooding routing strategy [10] is designed primarily to deal with network scalability and energy efficiency. The time tag is used to combine signal and flooding routing, which can reduce the signaling overheads. The above research results on routing strategies need to be further considered for the change of network topology. Since the scale of IoT applications and services is increasing day by day, the network topology is becoming more complex. The local topology is more complex and easy to change. As the wireless sensor nodes have limited computing and communications capabilities, the network will use an appropriate sleeping strategy to save node energy, which entails changing the network topology. In addition, both the sensor nodes and the entire sensor network are vulnerable to attacks. Therefore, resilient routing strategies are needed to handle the routing problem under changing network topology, whether caused by the sleeping scheme of the network or by an external attack. Inspired by this view, a failure-resilient routing strategy via IoT networks was proposed in [11]. The routing strategy in [11] can automatically explore and establish optimal local routes in the event that unpredictable failures cause the previous route to fail. In addition, the temporary rerouting will be abandoned when the failures have been repaired. A dynamic Attack-Resilient Routing (ARR) strategy was designed in [12] in software-defined networks. The ARR dynamically routes the data fragments through a set of reliable and lightly loaded paths to achieve multi-path diversity, thus improving the data availability of the destination in the presence of attacks. According to the above research results, multi-path routing in wireless sensor networks is one of the more effective methods to deal with network topology changes.