Multi-Agent DDPG-Based Joint Task Partitioning and Power Control in Fog Computing Networks

IEEE Internet of Things Journal ◽

10.1109/jiot.2021.3091508 ◽

2021 ◽

pp. 1-1

Author(s):

Zhipeng Cheng ◽

Minghui Min ◽

Minghui Liwang ◽

Lianfen Huang ◽

Zhibin Gao

Keyword(s):

Power Control ◽

Fog Computing ◽

Task Partitioning ◽

Download Full-text

Application of multi-agent approach in the electric power control systems within the active energy complex

Journal of Physics Conference Series ◽

10.1088/1742-6596/1694/1/012017 ◽

2020 ◽

Vol 1694 ◽

pp. 012017

Author(s):

A E Zhavoronkov ◽

O P Aksyonova

Keyword(s):

Power Control ◽

Electric Power ◽

Control Systems ◽

Energy Complex ◽

Download Full-text

A Multi-agent Reinforcement Learning Based Power Control Algorithm for D2D Communication Underlaying Cellular Networks

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering - Artificial Intelligence for Communications and Networks ◽

10.1007/978-3-030-22971-9_7 ◽

2019 ◽

pp. 77-90

Author(s):

Wentai Chen ◽

Jun Zheng

Keyword(s):

Reinforcement Learning ◽

Power Control ◽

Cellular Networks ◽

Control Algorithm ◽

D2d Communication ◽

Power Control Algorithm ◽

Download Full-text

Multi-agent approach to distributed processing big sensor data based on fog computing model for the monitoring of the urban infrastructure systems

2016 International Conference System Modeling & Advancement in Research Trends (SMART) ◽

10.1109/sysmart.2016.7894540 ◽

2016 ◽

Author(s):

Danila Parygin ◽

Nikita Nikitsky ◽

Valery Kamaev ◽

Anna Matokhina ◽

Alexey Finogeev ◽

...

Keyword(s):

Fog Computing ◽

Distributed Processing ◽

Urban Infrastructure ◽

Sensor Data ◽

Infrastructure Systems ◽

Computing Model ◽

Download Full-text

Reinforced resource management in vehicular fog computing using deep beacon power control protocol

International Journal of Web and Grid Services ◽

10.1504/ijwgs.2021.10040917 ◽

2021 ◽

Vol 17 (4) ◽

pp. 371

Author(s):

Seifedine Kadry ◽

S. Vimal ◽

Y. Harold Robinson ◽

E. Golden Julie ◽

R. Rajmohan ◽

...

Keyword(s):

Resource Management ◽

Power Control ◽

Fog Computing ◽

Control Protocol

Download Full-text

Multi-Agent Q-Learning Based Multi-UAV Wireless Networks for Maximizing Energy Efficiency: Deployment and Power Control Strategy Design

IEEE Internet of Things Journal ◽

10.1109/jiot.2021.3113128 ◽

2021 ◽

pp. 1-1

Author(s):

Seungmin Lee ◽

Heejung Yu ◽

Howon Lee

Keyword(s):

Energy Efficiency ◽

Wireless Networks ◽

Power Control ◽

Control Strategy ◽

Multi Agent ◽

Strategy Design ◽

Download Full-text

Power Control Based on Multi-Agent Deep Q Network for D2D Communication

2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) ◽

10.1109/icaiic48513.2020.9065192 ◽

2020 ◽

Author(s):

Shi Gengtian ◽

Takashi Koshimizu ◽

Megumi Saito ◽

Pan Zhenni ◽

Liu Jiang ◽

...

Keyword(s):

Power Control ◽

D2d Communication ◽

Download Full-text

MULTI-AGENT DATA PROCESSING IN FOG COMPUTING ENVIRONMENT IN WIRELESS SENSOR NETWORK

Vestnik komp iuternykh i informatsionnykh tekhnologii ◽

10.14489/vkit.2015.12.pp.037-043 ◽

2015 ◽

pp. 37-43

Author(s):

V. A. Kamaev ◽

А. G. Finogeev ◽

A. M. Bershadsky ◽

I. S. Nefedova ◽

E. A. Finogeev

Keyword(s):

Wireless Sensor Network ◽

Data Processing ◽

Sensor Network ◽

Fog Computing ◽

Wireless Sensor ◽

Computing Environment ◽

Download Full-text

A multi-agent based distributed reactive power control method

2009 IEEE Power & Energy Society General Meeting ◽

10.1109/pes.2009.5275445 ◽

2009 ◽

Author(s):

T. Nagata ◽

R. Hatano ◽

H. Saiki

Keyword(s):

Power Control ◽

Reactive Power ◽

Control Method ◽

Reactive Power Control ◽

Agent Based ◽

Download Full-text

Resource Allocation and Power Control Policy for Device-to-Device Communication Using Multi-Agent Reinforcement Learning

Computers Materials & Continua ◽

10.32604/cmc.2020.09130 ◽

2020 ◽

Vol 63 (3) ◽

pp. 1515-1532

Author(s):

Yifei Wei ◽

Yinxiang Qu ◽

Min Zhao ◽

Lianping Zhang ◽

F. Richard Yu

Keyword(s):

Resource Allocation ◽

Reinforcement Learning ◽

Power Control ◽

Control Policy ◽

Device To Device ◽

Multi Agent ◽

Device To Device Communication

Download Full-text

Distributed Power Control for Large Energy Harvesting Networks: A Multi-Agent Deep Reinforcement Learning Approach

IEEE Transactions on Cognitive Communications and Networking ◽

10.1109/tccn.2019.2949589 ◽

2019 ◽

Vol 5 (4) ◽

pp. 1140-1154 ◽

Author(s):

Mohit K. Sharma ◽

Alessio Zappone ◽

Mohamad Assaad ◽

Merouane Debbah ◽

Spyridon Vassilaras

Keyword(s):

Reinforcement Learning ◽

Energy Harvesting ◽

Power Control ◽

Large Energy ◽

Learning Approach ◽

Distributed Power ◽

Distributed Power Control ◽

Download Full-text