Open Access iconOpen Access

ARTICLE

crossmark

Fine-Grained Bandwidth Estimation for Smart Grid Communication Network

Jingtang Luo1, Jingru Liao2, Chenlin Zhang3, Ziqi Wang4, Yuhang Zhang2, Jie Xu2,*, Zhengwen Huang5

1 State Grid Sichuan Economic Research Institute, Chengdu, 610041, China
2 School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China
3 Science and Technology on Security Communication Laboratory, Institute of Southwestern Communication, Chengdu, 610093, China
4 State Grid Economic and Technological Research Institute CO., LTD, Beijing, 100055, China
5 Department of Electronic and Computer Engineering, Brunel University, Uxbridge, UB8 3PH, United Kingdom

* Corresponding Author: Jie Xu. Email: email

Intelligent Automation & Soft Computing 2022, 32(2), 1225-1239. https://doi.org/10.32604/iasc.2022.022812

Abstract

Accurate estimation of communication bandwidth is critical for the sensing and controlling applications of smart grid. Different from public network, the bandwidth requirements of smart grid communication network must be accurately estimated in prior to the deployment of applications or even the building of communication network. However, existing methods for smart grid usually model communication nodes in coarse-grained ways, so their estimations become inaccurate in scenarios where the same type of nodes have very different bandwidth requirements. To solve this issue, we propose a fine-grained estimation method based on multivariate nonlinear fitting. Firstly, we use linear fitting to calculate the convergence weights of each node. Then, we use correlation to select the important characteristics. Finally, we use multivariate nonlinear fitting to learn the nonlinear relationship between characteristics and convergence weight, and complete the fine-grained bandwidth estimation. Our method exploits multiple node characteristics to reveal how different nodes affect bandwidth requirements differently, and it can learn multivariate estimation parameters from present network without human interference. We use NS2 to simulate a real-world regional smart grid. Simulation shows that our method outperforms existing works by up to 56.5% higher estimation accuracy.

Keywords


Cite This Article

APA Style
Luo, J., Liao, J., Zhang, C., Wang, Z., Zhang, Y. et al. (2022). Fine-grained bandwidth estimation for smart grid communication network. Intelligent Automation & Soft Computing, 32(2), 1225-1239. https://doi.org/10.32604/iasc.2022.022812
Vancouver Style
Luo J, Liao J, Zhang C, Wang Z, Zhang Y, Xu J, et al. Fine-grained bandwidth estimation for smart grid communication network. Intell Automat Soft Comput . 2022;32(2):1225-1239 https://doi.org/10.32604/iasc.2022.022812
IEEE Style
J. Luo et al., "Fine-Grained Bandwidth Estimation for Smart Grid Communication Network," Intell. Automat. Soft Comput. , vol. 32, no. 2, pp. 1225-1239. 2022. https://doi.org/10.32604/iasc.2022.022812



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1403

    View

  • 1005

    Download

  • 0

    Like

Share Link