## 2 Methodology
### An Optimal Energy Resources Allocation Method Based on Clustering Optimization
#### 2.2.1 Clustering and Cluster Head Initialization Based on Improved K-Medoids
In this paper, we designed a double-layer communication network based on wireless sensor network for intelligent railway systems firstly. In the sub-network, routing protocol optimization strategy are adopted to optimize the allocation of energy resources, so as to improve the efficiency of energy resources utilization of the system and maximize the lifecycle of special wireless sensor networks. Compared with other existing methods, we proposed cluster head selection and initialization method based on improved K-medoids algorithm, which greatly improves the speed and effect of cluster optimization. At the same time, the proposed clustering optimization model is dynamic, it can make the sub-network maintain the optimal energy consumption for monitoring data transmission, so as to ensure that each cluster head node always works in the optimal energy consumption state. Although we had done some related work in energy optimization of railway wireless monitoring system, there are also limitations. First, the research in this paper is based on local information acquisition. However, railway systems are complex and huge systems. Single local information is far from enough for evaluating the overall performance of the system and predicting the overall security situation of the system. Second, the results of optimization in this paper are mainly validated based on laboratory data and simulation data. In order to meet the needs of field application, the next step is to collect actual monitoring data. Third, multi-objective optimization model is established to solve the optimization of energy resources utilization in this paper. In the future we will make full use

Figure 11: Relationship of coverage vector and network lifetime. of the historical data of railway systems and synthesize the machine learning method to solve the optimization problem for satisfying the real-time demand. Conceptualization, S.B., G.S. ; methodology, S.B., G.S. ; software, G.S. ; writing--original draft preparation, S.B. ; writing--review and editing, S.B., G.S. All authors have read and agreed to the published version of the manuscript. This research was funded by Shandong Provincial Natural Science Foundation, grant number ZR2017 MG011. The authors declare no conflict of interest. ## References

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