.png){kind=icon}
.png){kind=icon}
Return
Optical path failure protection in all-optical DCNs combining p-cycle and SVM learning via priority classification
.png){kind=icon}
PRE
AI
Z
Y
G
W
H
W
S
DOI：10.23919/jcc.fa.2025-0281.202604.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Conventional path protection algorithms in all-optical data center networks (DCNs) need a relatively long calculation time but with low efficiency. In this article, we propose a preset path recovery algorithm by combining machine learning and priority execution method. The former is to predict areas of frequent optical path failures in data centers, and the latter is to ensure accurate protection in those areas while reducing computation time and improving performance. Firstly, we construct a dataset using rules composed of topological edge relationships, failure time, failure frequency, packet loss rate, latency and service type. Then, based on the above dataset, SVM (support vector machine) algorithm is used to predict frequent failure areas. Finally, based on different prediction frequencies, priority construction is carried out to cluster the entire topology, and p-cycle (preconfigured protection cycle) is applied to each topology. Experiments show that the combination of SVM prediction and classification protection can significantly reduce the protection range of potential failure areas to reduce computation time while ensuring high accuracy, as compared with traditional optical path protection algorithms.
Keywords:
all-optical data center networks (DCNs)
optical path protection
p-cycle (preconfigured protection cycle)
SVM (support vector machine)
Journal
IF:
3.1
Papers:
1.8K
Citations:
5.0K
Organization
Cited Papers