# Delay-Sensitive Multi-Sensor Routing Scheduling Method for Underground IoT in Mines
## 3 System Modeling  
### Topology Structure of Underground IoT in Mines  
IoT devices are deployed along irregular tunnels in some complex construction environments with multiple tunnels, such as metal mining sites. As shown in Figure 1, in the process of gold mining, tunnels need to be excavated according to the distribution of veins, so the deployment of IoT devices will present a mesh topology along different tunnels. In Figure 1, the base stations are connected to each other via wired connections, while the sensor still sends data wirelessly. The base station and the sensor form a star topology, and the base station and the base station present a multi-hop network topology according to the actual situation of the tunnel. In this topology, both the reliability of wireless transmission and the path of multi-hop data transmission between base stations need to be considered to ensure that data are sent to the cloud between deadlines. Based on the IoT application scenario in underground construction, Figure 2 is a multi-sensor IoT application topology. In this topology, node F is the endpoint of the cloud device. The four base stations \(A,B,C\), and \(D\) form a mesh topology through a cable. The sensor (1, 2, 3,...) sends wireless data to the base station, and the base station needs to send data to the endpoint \(F\) through the multi-hop network topology. Assume that the No. 1 sensor of the base station \(A\) sends data to \(A\), and \(A\) can send data to \(F\) through multiple path selections. When the network does not consider other node data, the transmission problem is the shortest-path problem, which the shortest-path algorithm can solve. However, when other nodes in the network also need to send data, considering the delay caused by node caching, queuing, etc., how to send all data to focus \(F\) in the shortest time is a problem that needs to be studied such as in this paper. As shown in Figure 2, the next hop of the packet arriving from the base station \(A\) can select the base station \(C\) or the base station \(D\). After selecting the base station \(C\), the direct path to the destination base station is the shortest path. If base station \(A\) has only one data packet, and there is no other data packet except base station \(A\), this method can obtain the minimum delay. However, in practice, if all data packets choose the shortest path to reach the destination base station, such as base station \(A\) and base station \(B\), all data packets of the base station are through the base station \(C\), which will lead to congestion at the base station \(C\). Compared with the case where each data packet randomly selects the path based on not repeating the path, the delay will be higher. If all data packets are routed to the base  
Figure 1: The hardware deployment diagram of the IoT under the mine. Figure 2: Hybrid topological structure of mesh and star. station with the smallest load at the next hop, there will likely be an unnecessary detour. Assume that the load of the base station \(D\) is slightly smaller than that of the base station \(C\); a single data packet in the B base station will select the base station \(D\). Since the load of the next hop of base station \(D\) and the number of hops required cannot be known directly, the next-hop base station \(E\) of base station \(D\) may produce a higher delay after the base station \(D\) is selected by detour. As a result, the delay of a single packet is not as good as the shortest path. In scheduling, data packets will interact with each other. Using a fixed decision method to optimize the individual scheduling data packets in the front is likely to lead to a significant deterioration of the scheduling results of the data packets in the back of the scheduling problem. For example, it is assumed that the base station \(A\) has two packets with an arrival time of 0 and a deadline of 3. The base station \(E\) has one packet with an arrival time of 2 and a deadline of 1.