Deep Reinforcement Learning Based Resource Management for DNN Inference in IIoT

被引:0
作者
Zhang, Weiting [1 ]
Yang, Dong [1 ]
Peng, Haixia [2 ]
Wu, Wen [2 ]
Quan, Wei [1 ]
Zhang, Hongke [1 ]
Shen, Xuemin [2 ]
机构
[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing, Peoples R China
[2] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON, Canada
来源
2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM) | 2020年
基金
中国国家自然科学基金; 加拿大自然科学与工程研究理事会;
关键词
DNN inference; IIoT; resource management; deep deterministic policy gradient; EDGE; NETWORKS; INTERNET;
D O I
10.1109/GLOBECOM42002.2020.9322223
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we investigate the joint task assignment and resource allocation for deep neural network (DNN) inference in the device-edge-cloud based industrial Internet of things (IIoT) networks. To efficiently orchestrate the limited spectrum and computing resources in IIoT networks for massive DNN inference tasks, a resource management problem is formulated with the objective of maximizing the average inference accuracy while satisfying the quality-of-service of DNN inference tasks. Considering the strict delay requirements of inference tasks, we transform the formulated problem into a Markov decision process, and propose a deep deterministic policy gradient based learning algorithm to obtain the solution rapidly. Simulation results show that the proposed algorithm can achieve high average inference accuracy.
引用
收藏
页数:6
相关论文
共 50 条
[21]   Deep Reinforcement Learning Based Resource Allocation for LoRaWAN [J].
Li, Aohan .
2022 IEEE 96TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2022-FALL), 2022,
[22]   Blockchain-based Dependable Task Offloading and Resource Allocation for IIoT via Multi-Agent Deep Reinforcement Learning [J].
Zhang, Peifeng ;
Xu, Chi ;
Xia, Changqing ;
Jin, Xi .
2023 IEEE 98TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2023-FALL, 2023,
[23]   Multiagent Deep Reinforcement Learning for Task Offloading and Resource Allocation in Cybertwin-Based Networks [J].
Hou, Wenjing ;
Wen, Hong ;
Song, Huanhuan ;
Lei, Wenxin ;
Zhang, Wei .
IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (22) :16256-16268
[24]   Imperfect CSI-Based Resource Management in Cognitive IoT Networks: A Deep Recurrent Reinforcement Learning Framework [J].
Kaur, Amandeep ;
Kumar, Krishan ;
Prakash, Arun ;
Tripathi, Rajeev .
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 2023, 9 (05) :1271-1281
[25]   Analysis of Resource Management Methods Based on Reinforcement Learning [J].
Xing, Mingzhe ;
Wang, Ziyun ;
Xiao, Zhen .
2021 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE BIG DATA AND INTELLIGENT SYSTEMS (HPBD&IS), 2021, :27-31
[26]   Intelligent Cruise Guidance and Vehicle Resource Management With Deep Reinforcement Learning [J].
Sun, Guolin ;
Liu, Kai ;
Boateng, Gordon Owusu ;
Liu, Guisong ;
Jiang, Wei .
IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (05) :3574-3585
[27]   Network Resource Allocation Strategy Based on Deep Reinforcement Learning [J].
Zhang, Shidong ;
Wang, Chao ;
Zhang, Junsan ;
Duan, Youxiang ;
You, Xinhong ;
Zhang, Peiying .
IEEE OPEN JOURNAL OF THE COMPUTER SOCIETY, 2020, 1 (01) :86-94
[28]   Multi-Slot Secure Offloading and Resource Management in VEC Networks: A Deep Reinforcement Learning-Based Method [J].
Li, Zhen ;
Gong, Jialong ;
Xiong, Xiong ;
Wang, Dong .
IEEE ACCESS, 2025, 13 :4533-4546
[29]   Predictive Maintenance Model for IIoT-Based Manufacturing: A Transferable Deep Reinforcement Learning Approach [J].
Ong, Kevin Shen Hoong ;
Wang, Wenbo ;
Hieu, Nguyen Quang ;
Niyato, Dusit ;
Friedrichs, Thomas .
IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (17) :15725-15741
[30]   Smart Resource Allocation for Mobile Edge Computing: A Deep Reinforcement Learning Approach [J].
Wang, Jiadai ;
Zhao, Lei ;
Liu, Jiajia ;
Kato, Nei .
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING, 2021, 9 (03) :1529-1541