Abstract
With recent achievements in deep learning over the past year, many computer and network applications actively used deep learning architectures including convolution neural network and long short-term memory to improve the performance of their approach through them. The computer network used a complex and dynamic system. For example, routing is the main networking tasks in the fields of the communication network and it is widely used to optimize the optimal routing from the original host to the destination host. However, most of the traditional routing protocol is based on the experience of experts. In this paper, we present an overview of deep learning methods for the routing layer in the computer network. Furthermore, this paper discusses reinforcement learning methods about network routing. Finally, we outline a summary of the current state-of-the-art approaches along with some future research directions.
| Original language | English |
|---|---|
| Title of host publication | 2019 UK/China Emerging Technologies, UCET 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728127972 |
| DOIs | |
| State | Published - Aug 2019 |
| Externally published | Yes |
| Event | 2019 UK/China Emerging Technologies, UCET 2019 - Glasgow, Scotland, United Kingdom Duration: 21 Aug 2019 → 22 Aug 2019 |
Publication series
| Name | 2019 UK/China Emerging Technologies, UCET 2019 |
|---|
Conference
| Conference | 2019 UK/China Emerging Technologies, UCET 2019 |
|---|---|
| Country/Territory | United Kingdom |
| City | Glasgow, Scotland |
| Period | 21/08/19 → 22/08/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Computer network
- Deep learning
- Reinforcement learning
- Routing layer
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Information Systems and Management
- Energy Engineering and Power Technology
- Health Informatics
- Instrumentation
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