Energy-Saving Adaptive Routing for High-Speed Railway Monitoring Network Based on Improved Q Learning  
[PERSON]  
1  
[PERSON] and [PERSON]  
Key Laboratory of Industrial Internet of Things and Network Control, Ministry of Education,  
Chongqing University of Posts and Telecommunications, Chongqing 400065, China; [EMAIL_ADDRESS] (Q.P. ); [EMAIL_ADDRESS] (C.H.) 1  
Footnote 1  
field of high-speed train operation environment monitoring. The use of wireless systems to monitor the operating environment of high-speed railways can realize large-scale deployment along the railway, ensure the breadth and accuracy of data collection, and monitor the condition of slopes, tunnels, roadbeds, bridges, and other facilities, which can effectively meet the needs of high-speed trains. The need for comprehensive monitoring of the operating environment reduces the cost of train operating environment testing and is suitable for large-scale deployment and long-term online monitoring in key areas and remote areas along the high-speed railway. However, the energy resources of wireless devices are strictly limited. The greatest challenge in wireless sensor networks is determining a way to conserve energy, and the amount of time that the network lasts is a good measure of teh quality of its performance [8; 9]. In order to ensure the real-time performance of high-speed railway operating environment monitoring information and the energy utilization efficiency of the network system, a protocol that adapts to the characteristics of the high-speed railway operating environment monitoring network is needed to efficiently utilize the limited energy resources of the network system and provide more long-term energy efficiency [10]. The increase in communication distance increases the energy consumption of some nodes and shortens the network life. Each protocol chooses to increase the number of forwarding hops to achieve a balance of energy consumption, and the overall energy consumption is evenly distributed to more nodes to avoid premature death of some nodes. But the increase in hop count inevitably increases the delay of information transmission, which is bad news for the high-speed railway monitoring network [11; 12]. In fact, it is difficult to guarantee the real-time performance of the network and its maximum lifespan at the same time. Extending the lifespan and increasing the number of hops results in a large delay and affects the service quality of the monitoring network. To this end, in the intelligent high-speed railway monitoring system. The information in the network can be divided into several parts: receiving, transmitting, processing, state evaluation and prediction, and control decision-making. Generally speaking, the transmission of data along the shortest path can minimize the energy consumption of the network, but this approach introduces the problem of unbalanced energy consumption. The energy consumption of the sensor device closer to the sink node is faster, which is the so-called energy hole phenomenon [13; 14; 15]. This phenomenon destroys the balance of energy consumption among nodes, affects the life of the network, and also has a negative impact on the real-time performance of data transmission, hindering the normal service of the network system. Therefore, in addition to minimizing the network energy consumption, the energy consumption balance among network nodes should also be considered when designing the routing algorithm to extend the life of the network system. Therefore, when designing a routing protocol for a high-speed railway operation environment monitoring network, it is necessary to minimize and balance network energy consumption while reducing data transmission delay so as to improve real-time performance and network energy utilization, and prolong network service life. Therefore, the goal of this paper is to look into ways in which a high-speed railway operation environment monitoring network can use an adaptive routing method to meet the needs of different services [16; 17].