Dynamic Routing and Wavelength Assignment with Reinforcement Learning Article Swipe
Peyman Kafaei
,
Quentin Cappart
,
Nicolas Chapados
,
Hamed Pouya
,
Louis-Martin Rousseau
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1287/ijoo.2023.0092
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1287/ijoo.2023.0092
With the rapid developments in communication systems, and considering their dynamic nature, all-optical networks are becoming increasingly complex. This study proposes a novel method based on deep reinforcement learning for the routing and wavelength assignment problem in all-optical wavelength-decision-multiplexing networks. We consider dynamic incoming requests, in which their arrival and holding times are not known in advance. The objective is to devise a strategy that minimizes the number of rejected packages due to the lack of resources in the long term. We use graph neural networks to capture crucial latent information from the graph-structured input to develop the optimal strategy. The proposed deep reinforcement learning algorithm selects a route and a wavelength simultaneously for each incoming traffic connection as they arrive. The results demonstrate that the learned agent outperforms the methods used in practice and can be generalized on network topologies that did not participate in training.
Related Topics
Concepts
Reinforcement learning
Computer science
Adaptive routing
Routing and wavelength assignment
Network topology
Routing (electronic design automation)
Graph
Wavelength-division multiplexing
Artificial intelligence
Distributed computing
Computer network
Static routing
Wavelength
Theoretical computer science
Routing protocol
Optoelectronics
Physics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1287/ijoo.2023.0092
- OA Status
- diamond
- Cited By
- 5
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4380051626
All OpenAlex metadata
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https://openalex.org/W4380051626Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1287/ijoo.2023.0092Digital Object Identifier
- Title
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Dynamic Routing and Wavelength Assignment with Reinforcement LearningWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-06-08Full publication date if available
- Authors
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Peyman Kafaei, Quentin Cappart, Nicolas Chapados, Hamed Pouya, Louis-Martin RousseauList of authors in order
- Landing page
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https://doi.org/10.1287/ijoo.2023.0092Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1287/ijoo.2023.0092Direct OA link when available
- Concepts
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Reinforcement learning, Computer science, Adaptive routing, Routing and wavelength assignment, Network topology, Routing (electronic design automation), Graph, Wavelength-division multiplexing, Artificial intelligence, Distributed computing, Computer network, Static routing, Wavelength, Theoretical computer science, Routing protocol, Optoelectronics, PhysicsTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
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2025: 4, 2024: 1Per-year citation counts (last 5 years)
- References (count)
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10Other works algorithmically related by OpenAlex
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