# Energy-Efficient Opportunistic Routing Algorithm for Post-Disaster Mine Internet of Things Networks
## 2 Related Work
### MIoT Routing Protocols  
Here, we briefly present some existing well-known routing protocols for MIoT networks. A comparison of the protocols is listed in Table 1.  
On the one hand, several routing protocols (e.g., [13; 14; 15]) were proposed to enhance the performance of data transmission in normal coal mine tunnels. [PERSON] et al. [13] proposed a Routing Protocol in mine roadways based on Area Positive Clustering and Mobile Nodes (RPAPC-MN). In RPAPC-MN, an area-positive clustering mechanism is applied to avoid data re-entry. By utilizing nodes equipped with miners and mobile equipment to forward data, RPAPC-MN reduces energy consumption and extends the network lifetime. [PERSON] et al. [14] proposed a Differential Evolution routing (DE) protocol for wireless multimedia sensor networks for underground mines. By setting different weights in the normalized sub-QoS evaluation function of transmission delay, packet loss rate, and transmission energy consumption and applying the marking method to obtain the transmission path, DE offers a differentiated service and guarantees the QoS for multimedia services. [PERSON] et al. [15] proposed an Optimal Forwarding Algorithm (OFA) for coal mine WSNs. When sensor nodes are evenly deployed in narrow lanes, OFA can dynamically adjust the node's forwarded data volume and forwarded routing to balance the node energy consumption and maximize the network life cycle. On the other hand, a number of routing protocols (e.g., [16; 17; 18; 19; 20]) were proposed to restore reliable data transmission in mine tunnels after disasters. [PERSON] et al. [16] proposeda Self-organized Energy-efficient Clustering (SEC) protocol for post-disaster reconstructed MIoT networks. SEC designs the election probability function based on the energy factor and connectivity factor. In SEC, the cluster head (CH) node was replaced by periodically comparing the residual energy and the threshold energy, which reduced the overall energy consumption and improved the stability of reconfiguration networks. On this basis, [PERSON] et al. [17] proposed an Energy-balanced Adaptive Uneven Clustering (EAUC) to solve the issue of node energy heterogeneity after disasters. EAUC introduces the CH election threshold function according to residual energy, relative distance, and distribution density of surviving nodes. The weight function of the relay CH was built by considering the current residual energy of the relay CH, and the CH with the largest weight was selected as the next hop routing node. [PERSON] et al. [18] proposed a post-disaster reconstruction algorithm of a wireless ad hoc network in coal mines based on the Multi-dimensional Virtual Backbone Network (MVBN). The MVBN constructs a comprehensive evaluation index of virtual backbone nodes by considering betweenness centrality, node closeness, and residual energy. In the MVBN, nodes with a large evaluation index are elected as dominant nodes, so as to enhance the robustness of the virtual backbone network and prolong the network's lifetime. [PERSON] et al. [19] proposed a Network Hole Coverage Reconstruction Algorithm with Obstacles (NHCRA-O) for post-disaster MIoT. In NHCRA-O, Delaunay triangulation is used to divide residual nodes and corner points of obstacles in the network. The virtual repair node position is determined through the distance between the centroid and the vertex of the Delaunay triangle. NHCRA-O selects CHs according to the residual energy factor, node connectivity and directional betweenness, which significantly extends the network lifespan. [PERSON] [20] proposed an energy-balanced Routing protocol based on the Improved Ant Colony algorithm (RIAC) to address the problem of uneven energy consumption between network clusters after disasters. RIAC introduces residual energy, distance, and node trust factors based on the traditional ant colony algorithm. By modifying the transition probability formula, pheromone heuristic function, and pheromone update strategy, RIAC realizes the optimal path selection from the CH to the base station.