Author
Listed:
- Jianrong Wang
- Pan Zhang
- Wei Bai
- Guoyuan Yang
- Yunyun Yang
Abstract
In the future, the Internet of things will reduce the cell radius and increase the number of low-power nodes to support thousands of times of traffic growth under 5G. As a virtual multiple input multiple output technology, cooperative communication technology can solve these problems effectively. According to the evolution characteristics of cooperative communication networks, a multi-domain cooperative communication network evolution model with preferential attachment and random attachment is constructed in this article. And then, the network properties and robustness are analyzed using the mean-field method and different attacks. Aiming at the resource constraints and resource allocation problems of communication nodes, a relay selection strategy based on the combination of maximum degree and minimum clustering coefficient is proposed. The simulation results show that the relay node selection strategy based on the combination of maximum degree and minimum clustering coefficient has significant advantages in selection steps and selection time, which greatly enhanced the performance of relay selection in multi-domain cooperative communication networks. Through real-time monitoring and updating of the performance and security indicators of the multi-domain cooperative communication networks, it provides a strong guarantee for the node deployment and security management of the Internet of things cooperative communication system.
Suggested Citation
Jianrong Wang & Pan Zhang & Wei Bai & Guoyuan Yang & Yunyun Yang, 2022.
"Evolutionary modeling and robustness analysis of multi-domain cooperative communication network under the environment of Internet of things,"
International Journal of Distributed Sensor Networks, , vol. 18(11), pages 15501329221, November.
Handle:
RePEc:sae:intdis:v:18:y:2022:i:11:p:15501329221135160
DOI: 10.1177/15501329221135160
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:intdis:v:18:y:2022:i:11:p:15501329221135160. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.