research-article

A Deep Reinforcement Learning based Network Management System in Smart Identifier Network

Authors:

Shihua Chen,

Jia Chen,

Jing ChenAuthors Info & Claims

ICDSP '20: Proceedings of the 2020 4th International Conference on Digital Signal Processing

Pages 268 - 273

https://doi.org/10.1145/3408127.3408173

Published: 10 September 2020 Publication History

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Abstract

As a new large-scale deployment network, Smart Identifier Network (SINET) points out the identity/location binding, which is one of the root causes of current Internet's problem. In order to ensure the controllable manageability and large-scale deployment of the SINET, a network management system is of great essence. And considering the single point of failure of centralized network management, this paper proposes a Deep Reinforcement Learning (DRL) based domain network management system to manage the devices and achieve the reasonable allocation of management resources, where we consider the problem as a Markov Decision Process (MDP), including how to settle the new device and the change of the number of devices in each management domain at each time. By quantifying the cost function, we want to minimize it in a period of time, that is, to maximize the long-term expected reward value. The experiments show that our agent can automatically learn the environment, and the results will gradually reach convergence after certain iterations.

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Lim Meng Kee HAhmad NAzri Mohd Izhar MAnwar KNg S(2024)A Review on Machine Learning for Channel CodingIEEE Access10.1109/ACCESS.2024.341219212(89002-89025)Online publication date: 2024
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Zheng ZJiang SFeng RGe LGu C(2023)Survey of Reinforcement-Learning-Based MAC Protocols for Wireless Ad Hoc Networks with a MAC Reference ModelEntropy10.3390/e2501010125:1(101)Online publication date: 3-Jan-2023
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Abbasi MShahraki AJalil Piran MTaherkordi A(2021)Deep Reinforcement Learning for QoS provisioning at the MAC layer: A SurveyEngineering Applications of Artificial Intelligence10.1016/j.engappai.2021.104234102(104234)Online publication date: Jun-2021
https://doi.org/10.1016/j.engappai.2021.104234

Index Terms

A Deep Reinforcement Learning based Network Management System in Smart Identifier Network
1. Networks
  1. Network services
    1. Network management

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ICDSP '20: Proceedings of the 2020 4th International Conference on Digital Signal Processing

June 2020

383 pages

ISBN:9781450376877

DOI:10.1145/3408127

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 10 September 2020

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nature and science foundation of China
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ICDSP 2020

ICDSP 2020: 2020 4th International Conference on Digital Signal Processing

June 19 - 21, 2020

Chengdu, China

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Lim Meng Kee HAhmad NAzri Mohd Izhar MAnwar KNg S(2024)A Review on Machine Learning for Channel CodingIEEE Access10.1109/ACCESS.2024.341219212(89002-89025)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3412192
Zheng ZJiang SFeng RGe LGu C(2023)Survey of Reinforcement-Learning-Based MAC Protocols for Wireless Ad Hoc Networks with a MAC Reference ModelEntropy10.3390/e2501010125:1(101)Online publication date: 3-Jan-2023
https://doi.org/10.3390/e25010101
Abbasi MShahraki AJalil Piran MTaherkordi A(2021)Deep Reinforcement Learning for QoS provisioning at the MAC layer: A SurveyEngineering Applications of Artificial Intelligence10.1016/j.engappai.2021.104234102(104234)Online publication date: Jun-2021
https://doi.org/10.1016/j.engappai.2021.104234

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Deep Reinforcement Learning: From Q-Learning to Deep Q-Learning

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