基于人工智能算法的OTN时延数据优化与路径规划研究  

Research on OTN delay data optimization and path planning based on AI algorithm

作　　者：吴邦毅 WU Bangyi(China Telecom Fujian Branch,Fuzhou 350001,China)

机构地区：[1]中国电信股份有限公司福建分公司,福建福州350001

出　　处：《无线互联科技》2024年第11期117-119,共3页Wireless Internet Technology

摘　　要：随着数字经济的发展,各行各业对低时延的需求场景日益增多,在这种情况下,传输业务时延的准确性和完整性愈加重要。文章基于OTN光传送网络特性,提出了一种利用人工智能算法优化OTN时延数据与路径规划的方法。该方法通过对历史数据的深入学习和分析,构建预测网络时延变化趋势的回归模型,实现时延数据的快速补全。同时,文章依托完善的资源数据,结合人工智能搜索算法进行最优时延路径规划,为资源优化及路径规划应用提供了广泛而实用的解决方案。With the development of the digital economy,the demand for low latency scenarios is increasing in various industries.In this case,the accuracy and integrity of transmission business latency are becoming more important.Based on the characteristics of OTN optical transport network,this paper proposes a method to optimize OTN latency data and path planning using artificial intelligence algorithms.This method constructs a regression model to predict the trend of network latency changes through deep learning and analysis of historical data,so as to achieve rapid completion of latency data.At the same time,this paper relies on complete resource data and combines artificial intelligence search algorithms to carry out optimal latency path planning,providing a wide range of practical solutions for resource optimization and path planning applications.

关 键 词：OTN 时延估算 决策树回归 路由规划 启发式搜索 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]