Energy Efficient Task allocation for Distributed Multi-agent System

被引：0

作者：

Kim, Seonghyun ^{[1
]}

Jang, Ingook ^{[1
]}

Son, Youngsung ^{[1
]}

机构：

[1] Elect & Telecommun Res Inst, Daejeon, South Korea

来源：

2018 INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC) | 2018年

关键词：

Internet of things; multi-agent system; task allocation; energy efficiency; lifetime;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

According to increase flexibility and capability of devices by development of processing and communication abilities, a multi-agent system (MAS), which is one of the internet of things area, has been actively researched for distributed network environment. In this work, we present a strategy named energy efficient task allocation for multi-agent system (E2T-MAS) in order to maximize the lifetime of MAS over the distributed network The proposed E2T-MAS obtains not only the energy efficient task allocation but also an efficient communication power control with respect to residual energy and the link capacity of distributed multiple agents. Through the performance comparison, it is verified that the proposed scheme fairly distributes the energy consumption over the agents, and maximizes the lifetime of the MAS for a given time constraint in the system.

引用

页码：1034 / 1036

页数：3

共 50 条

[21] Learning Task Allocation for Multiple Flows in Multi-agent Systems [J].

Xiao, Zheng ;

Ma, Shengxiang ;

Zhang, Shiyong .

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMMUNICATION SOFTWARE AND NETWORKS, 2009, :153-157

[22] Distributed multi-agent coalition task allocation strategy for single pilot operation mode based on DQN [J].

Dong L. ;

Chen H. ;

Chen X. ;

Zhao C. .

Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica, 2023, 44 (13)

[23] Coordination control for distributed energy based on multi-agent system [J].

Zheng Y. ;

Shi Y. ;

Luo Y. ;

Gan Z. .

Shi, Yixiang (shyx@mail.tsinghua.edu.cn), 1600, Chinese Academy of Sciences (62) :3711-3718

[24] Task Allocation and Evaluation Model for Holonic Manufacturing System Based on Multi-agent System [J].

Zhao, Fuqing ;

Zhang, Qiuyu ;

Wang, Lianxiang .

2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, :4906-+

[25] Multi-Agent Aviation Search Task Allocation Method [J].

Wang Yijuan ;

Pan Weijun ;

Liu Kaiyuan .

2019 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS AND TECHNOLOGIES (AIAAT 2019), 2019, 646

[26] Multi-agent Deep Reinforcement Learning for Task Allocation in Dynamic Environment [J].

Ben Noureddine, Dhouha ;

Gharbi, Atef ;

Ben Ahmed, Samir .

ICSOFT: PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON SOFTWARE TECHNOLOGIES, 2017, :17-26

[27] Efficient Task Allocation in Multi-Agent Systems Using Reinforcement Learning and Genetic Algorithm [J].

Fang, Zheng ;

Ma, Tao ;

Huang, Jun ;

Niu, Zhao ;

Yang, Fang .

APPLIED SCIENCES-BASEL, 2025, 15 (04)

[28] Task Allocation for Multi-Agent Systems Based on Distributed Many-Objective Evolutionary Algorithm and Greedy Algorithm [J].

Zhou, Jing ;

Zhao, Xiaozhe ;

Zhang, Xiaopan ;

Zhao, Dongdong ;

Li, Huanhuan .

IEEE ACCESS, 2020, 8 :19306-19318

[29] Applying Machine Learning in Designing Distributed Auction for Multi-agent Task Allocation with Budget Constraints [J].

Luo, Chen ;

Huang, Qinwei ;

Kong, Fanxin ;

Khan, Simon ;

Qiu, Qinru .

2021 20TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS (ICAR), 2021, :356-363

[30] Distributed Task Allocation with Time Constraints under Limited Communication Resources 1n Multi-Agent System [J].

Li, Weilin ;

Wu, Jing ;

Long, Chengnian .

2024 14TH ASIAN CONTROL CONFERENCE, ASCC 2024, 2024, :2396-2401

← 1 2 3 4 5 →