Re-routing Computation Model and Optimization for Optical Layer ASON Networks

Chao Fujun; Jing Ruiquan

doi:10.11959/j.issn.1000-0801.DXKX260260

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Re-routing Computation Model and Optimization for Optical Layer ASON Networks

更新时间：2026-09-29

- Re-routing Computation Model and Optimization for Optical Layer ASON Networks
- Telecommunications Science (2026)
- 作者机构：
  
  1.中国电信股份有限公司山东分公司，山东济南250101
  2.中国电信股份有限公司研究院，北京102209
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.DXKX260260
  CLC： TN929.11
- Received：24 April 2026，
  
  Revised：2026-07-05，
  
  Accepted：02 September 2026，
- 稿件说明：
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Chao Fujun, Jing Ruiquan. Re-routing Computation Model and Optimization for Optical Layer ASON Networks[J/OL]. Telecommunications Science, 2026.
DOI：

Chao Fujun, Jing Ruiquan. Re-routing Computation Model and Optimization for Optical Layer ASON Networks[J/OL]. Telecommunications Science, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260260.

摘要

省干ROADM（可重构光分插复用）网络在光层ASON（自动交换光网络）环境下面临重路由成功率低、恢复时长过长的问题，本文建立面向多维度网络健康度的重路由计算模型，以提升光层ASON网络的重路由恢复能力与业务可用性。分析光层ASON网络架构与重路由机制，将OTS（光传输段）、OMS（光复用段）、OCH（光通道）三层光性能参数与波道资源利用率纳入路由计算，提出融合K最短路径（K-Shortest Path

K-SP）算法与光性能预评估的两阶段约束路由计算方法，给出资源预警阈值、性能整改标准及路由优先级调度策略，建立路径代价函数与优先级调度模型。基于某运营商省干ROADM网络的实测数据，对网络进行光性能整改和资源优化，验证结果表明：业务重路由首次成功率由81.14%提升至93.23%，1分钟内恢复的业务占比由65.59%提升至89.72%，超过5分钟中断的业务占比由5.13%降至0%，业务可用率由99.72%提升至99.86%。该模型可约束候选路径的光性能可行性，在资源紧张时优先保障高价值业务恢复。

Abstract

Provincial backbone ROADM (Reconfigurable Optical Add-Drop Multiplexer) networks under the optical layer ASON (Automatically Switched Optical Network) environment face the problems of low re-routing success rate and prolonged recovery time. This paper establishes a multi-dimensional network health-oriented re-routing computation model to improve the re-routing recovery capability and service availability of optical layer ASON networks. By analyzing the optical layer ASON architecture and re-routing mechanisms

the three-layer optical performance parameters—OTS (Optical Transmission Section)

OMS (Optical Multiplex Section)

and OCH (Optical Channel)—along with wavelength resource utilization are incorporated into routing computation. A two-stage constrained routing computation method that combines the K-shortest path (KSP) algorithm with optical performance pre-evaluation is proposed

along with resource warning thresholds

performance rectification standards

and route priority scheduling strategies. A path cost function and a priority scheduling model are also established. Validation using measured data from a provincial backbone ROADM network shows that after optimization

the first-time re-routing success rate increased from 81.14% to 93.23%

the proportion of services recovered within 1 minute rose from 65.59% to 89.72%

the proportion of interruptions exceeding 5 minutes dropped from 5.13% to 0%

and the service availability rate improved from 99.72% to 99.86%. The model constrains the optical performance feasibility of candidate paths and prioritizes high-value service recovery under resource-constrained scenarios.

关键词

Keywords

references

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