On-demand intelligent routing technology for deterministic network

Deterministic network needs to ensure the deterministic transmission requirements of different applications in terms of delay, packet loss rate, jitter, throughput, and reliability.In response to the differentiated and deterministic network transmission requirements of applications, an on-demand int...

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Main Authors: Zhongli WU, Yuanyuan CAO, Wenrui HUANG, Bin DAI, Yijun MO
Format: Article
Language:zho
Published: Beijing Xintong Media Co., Ltd 2021-11-01
Series:Dianxin kexue
Subjects:
Online Access:http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021245/
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author Zhongli WU
Yuanyuan CAO
Wenrui HUANG
Bin DAI
Yijun MO
author_facet Zhongli WU
Yuanyuan CAO
Wenrui HUANG
Bin DAI
Yijun MO
author_sort Zhongli WU
collection DOAJ
description Deterministic network needs to ensure the deterministic transmission requirements of different applications in terms of delay, packet loss rate, jitter, throughput, and reliability.In response to the differentiated and deterministic network transmission requirements of applications, an on-demand intelligent routing framework OdR for deterministic network was proposed.Under the OdR framework, an on-demand intelligent routing algorithm named OdR-TD3 based on deep reinforcement learning was proposed, which generates routing strategies based on the deterministic QoS requirements of application traffic, to satisfy the applications’ requirements of deterministic network.The experimental evaluation results show the OdR-TD3 algorithm has a significant advantage over the DV algorithm and the SPF algorithm in terms of the achievement rate of deterministic QoS requirements.
format Article
id doaj-art-a1aa69db5f9447fdbc44599e933613cd
institution Kabale University
issn 1000-0801
language zho
publishDate 2021-11-01
publisher Beijing Xintong Media Co., Ltd
record_format Article
series Dianxin kexue
spelling doaj-art-a1aa69db5f9447fdbc44599e933613cd2025-01-15T03:33:00ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012021-11-0137111659815769On-demand intelligent routing technology for deterministic networkZhongli WUYuanyuan CAOWenrui HUANGBin DAIYijun MODeterministic network needs to ensure the deterministic transmission requirements of different applications in terms of delay, packet loss rate, jitter, throughput, and reliability.In response to the differentiated and deterministic network transmission requirements of applications, an on-demand intelligent routing framework OdR for deterministic network was proposed.Under the OdR framework, an on-demand intelligent routing algorithm named OdR-TD3 based on deep reinforcement learning was proposed, which generates routing strategies based on the deterministic QoS requirements of application traffic, to satisfy the applications’ requirements of deterministic network.The experimental evaluation results show the OdR-TD3 algorithm has a significant advantage over the DV algorithm and the SPF algorithm in terms of the achievement rate of deterministic QoS requirements.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021245/deterministic networkdeep reinforcement learningon-demand intelligent routingquality of service
spellingShingle Zhongli WU
Yuanyuan CAO
Wenrui HUANG
Bin DAI
Yijun MO
On-demand intelligent routing technology for deterministic network
Dianxin kexue
deterministic network
deep reinforcement learning
on-demand intelligent routing
quality of service
title On-demand intelligent routing technology for deterministic network
title_full On-demand intelligent routing technology for deterministic network
title_fullStr On-demand intelligent routing technology for deterministic network
title_full_unstemmed On-demand intelligent routing technology for deterministic network
title_short On-demand intelligent routing technology for deterministic network
title_sort on demand intelligent routing technology for deterministic network
topic deterministic network
deep reinforcement learning
on-demand intelligent routing
quality of service
url http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021245/
work_keys_str_mv AT zhongliwu ondemandintelligentroutingtechnologyfordeterministicnetwork
AT yuanyuancao ondemandintelligentroutingtechnologyfordeterministicnetwork
AT wenruihuang ondemandintelligentroutingtechnologyfordeterministicnetwork
AT bindai ondemandintelligentroutingtechnologyfordeterministicnetwork
AT yijunmo ondemandintelligentroutingtechnologyfordeterministicnetwork