Latency-Aware Routing and Spectrum Assignment with Deep Reinforcement Learning

被引：0

作者：

Hernandez-Chulde, Carlos ^{[1
]}

Casellas, Ramon ^{[1
]}

Martinez, Ricardo ^{[1
]}

Vilalta, Ricard ^{[1
]}

Munoz, Raul ^{[1
]}

机构：

[1] Ctr Tecnol Telecomunicac Catalunya CTTC CERCA, Castelldefels, Barcelona, Spain

来源：

2022 18TH INTERNATIONAL CONFERENCE ON THE DESIGN OF RELIABLE COMMUNICATION NETWORKS (DRCN) | 2022年

关键词：

Deep reinforcement learning; elastic optical networks; routing and spectrum assignment; OPTICAL NETWORKS;

D O I：

10.1109/DRCN53993.2022.9758014

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper evaluates different aspects of the performance of a solution for routing and spectrum allocation in elastic optical networks. The evaluation includes the experimentation under different traffic loads and the use of a previously trained deep reinforcement learning (DRL) agent. The obtained results show that the DRL agent further outperforms a traditional algorithm as network resources become scarce. Moreover, the results show the proper operation of the pre-trained agent when provisioning lightpaths.

引用

页数：4

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