School of Software Engineering, JinLing Institute of Technology, Nanjing 211169, China.
Comput Intell Neurosci. 2022 Mar 24;2022:9450393. doi: 10.1155/2022/9450393. eCollection 2022.
With the development of communication technology, train control operation system develops gradually, which significantly improves the reliability and efficiency of train operation. The current mobile Internet has gradually highlighted the many limitations of the mobile Internet in the high-speed mobile environment, which seriously deteriorate the service quality and user experience, and cause a waste of resources. In order to meet the real-time requirements of network communication resource scheduling in the mobile environment, aiming at the multidimensional dynamic adaptation framework constructed in a mobile environment, a service and network adaptation mechanism based on link failure state prediction is proposed in the paper. First, cross-layer theoretical analysis and actual data analysis are combined to construct a wireless link failure probability model. Then, reliable transmission requirements and transmission overhead are applied to optimize goals. Finally, simulation experiments are carried out according to the railway network data to evaluate the E-GCF adaptation algorithm. The experiment results show that compared with the current mainstream algorithms, the prediction accuracy of this adaptation algorithm is improved by 25%. The execution time of the algorithm is reduced by 9.6 seconds and the successful submission rate is as high as 99.99%. The advantages of the algorithm are significantly superior other algorithms. It proves that the research method of this paper can effectively improve the satisfaction rate and utility value of reliable transmission, as well as enhance the throughput performance. It solves the adaptation problems of frequent switching and low utilization of heterogeneous networks in a mobile environment, which contributes to the high-quality communication service of mobile network.
随着通信技术的发展，列车控制操作系统逐渐发展，显著提高了列车运行的可靠性和效率。当前的移动互联网已经逐渐凸显出其在高速移动环境中的诸多局限性，严重恶化了服务质量和用户体验，并造成资源浪费。为了满足移动环境中网络通信资源调度的实时性要求，针对移动环境中构建的多维动态自适应框架，本文提出了一种基于链路故障状态预测的服务和网络自适应机制。首先，结合跨层理论分析和实际数据分析，构建了无线链路故障概率模型。然后，应用可靠传输要求和传输开销进行优化目标。最后，根据铁路网络数据进行了仿真实验，以评估 E-GCF 自适应算法。实验结果表明，与当前主流算法相比，该自适应算法的预测精度提高了 25%。算法的执行时间减少了 9.6 秒，提交成功率高达 99.99%。该算法的优势明显优于其他算法。这证明了本文的研究方法可以有效提高可靠传输的满意度和实用价值，增强吞吐量性能。它解决了移动环境中异构网络频繁切换和利用率低的自适应问题，有助于实现移动网络的高质量通信服务。
