Dynamic Resource Allocation for Power Distribution Internet of Things: a Game-Theoretic Model

被引:1
作者
Li, Zhi [1 ]
Liu, Zhu [1 ]
Liu, Yanzhu [2 ]
Zhang, Nan [1 ]
Guo, Jing [3 ]
机构
[1] State Grid Informat & Telecommun Grp Co Ltd, Beijing 102211, Peoples R China
[2] Great Wall Comp Software & Syst Inc, Beijing 100190, Peoples R China
[3] Aostar Informat Technol Co Ltd, Chengdu 610041, Peoples R China
来源
PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021) | 2021年
关键词
PD-IoT; Resource Allocation; Edge-Cloud collaboration; Game Theory; feedback Nash equilibrium;
D O I
10.1109/CCDC52312.2021.9601557
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the rapid development of smart terminals and sensors, the data scale of Power Distribution Internet of Things is increasing exponentially. The types of data are becoming more and more abundant. Processing and applying these data have become a hot spot in the industry and academia. Based on the Edge-Cloud Collaboration Architecture, the Power Distribution Internet of Things takes the Edge Internet of things Agent equipment as the core to realize the comprehensive perception, data fusion and intelligent application of the distribution network, thus effectively supporting the rapid development of the energy Internet. However, compared to Cloud Data Centers, the virtual computing resources of Edge IoT Agents are limited. To adapt the different service requirements, the Power Distribution Internet of Things system must coordinate limited virtual computing resources to improve the utilization of cloud and edge resources, thereby improving the quality of user services. In this paper, based on the research of the Power Distribution Internet of Things system architecture, a Four-Tier network model of the Power Distribution Internet of Things in the Edge-Cloud collaboration environment is constructed. Starting from the overall benefits of the Power Distribution Internet of Things system, an Edge-Cloud collaborative virtual computing resource allocation game model is constructed. Based on the dynamic differential game theory, the feedback Nash equilibrium solution of the dynamic game model is also proved and solved. Finally, the dynamic resource allocation model's effectiveness verified through simulation and evaluated its performance in an experimental environment.
引用
收藏
页码:1396 / 1400
页数:5
相关论文
共 12 条
[1]   Fog at the Edge: Experiences Building an Edge Computing Platform [J].
Giang, Nam Ky ;
Lea, Rodger ;
Blackstock, Michael ;
Leung, Victor C. M. .
2018 IEEE INTERNATIONAL CONFERENCE ON EDGE COMPUTING (IEEE EDGE), 2018, :9-16
[2]   Edge computing: A survey [J].
Khan, Wazir Zada ;
Ahmed, Ejaz ;
Hakak, Saqib ;
Yaqoob, Ibrar ;
Ahmed, Arif .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 97 :219-235
[3]   HoloDoc: Enabling Mixed Reality Workspaces that Harness Physical and Digital Content [J].
Li, Zhen ;
Annett, Michelle ;
Hinckley, Ken ;
Singh, Karan ;
Wigdor, Daniel .
CHI 2019: PROCEEDINGS OF THE 2019 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2019,
[4]   Incentive mechanism for computation offloading using edge computing: A Stackelberg game approach [J].
Liu, Yang ;
Xu, Changqiao ;
Zhan, Yufeng ;
Liu, Zhixin ;
Guan, Jianfeng ;
Zhang, Hongke .
COMPUTER NETWORKS, 2017, 129 :399-409
[5]  
SAMIE F, 2019, IoT for Smart Grids, P21, DOI DOI 10.1007/978-3-030-03640-9_2
[6]  
Santos GL, 2019, WILEY SER PARA DIST, P51
[7]   An Approach to QoS-based Task Distribution in Edge Computing Networks for IoT Applications [J].
Song, Yaozhong ;
Yau, Stephen S. ;
Yu, Ruozhou ;
Zhang, Xiang ;
Xue, Guoliang .
2017 IEEE 1ST INTERNATIONAL CONFERENCE ON EDGE COMPUTING (IEEE EDGE), 2017, :32-39
[8]   Offloading in Internet of Vehicles: A Fog-Enabled Real-Time Traffic Management System [J].
Wang, Xiaojie ;
Ning, Zhaolong ;
Wang, Lei .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (10) :4568-4578
[9]   An energy-aware computation offloading method for smart edge computing in wireless metropolitan area networks [J].
Xu, Xiaolong ;
Li, Yuancheng ;
Huang, Tao ;
Xue, Yuan ;
Peng, Kai ;
Qi, Lianyong ;
Dou, Wanchun .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2019, 133 :75-85
[10]  
Yeung D. W. K., 2006, SPRING S OPERAT RES