Application of 5G network slicing technology in smart grid

Author(s):  
Ran Liu ◽  
Xingyuan Hai ◽  
Siwei Du ◽  
Lingkang Zeng ◽  
Jie Bai ◽  
...  
Author(s):  
Ma Limeng ◽  
Zhang Ningchi ◽  
Kong Xiangyu ◽  
Zhu Yukun ◽  
Wang Yanru ◽  
...  

2021 ◽  
Vol 791 (1) ◽  
pp. 012128
Author(s):  
Hongliang Wei ◽  
Guohui Chen ◽  
Yizhu Zhang ◽  
Chao Guo ◽  
Shuo Shi ◽  
...  

2021 ◽  
Vol 2078 (1) ◽  
pp. 012077
Author(s):  
Dongwu ◽  
Zhangtao ◽  
Chenxiaojin ◽  
Zhuhailong ◽  
Pengdili

Abstract With the continuous construction and development of domestic power grids, the state has put forward many effective strategies to achieve the effectiveness and durability of energy supply, in order to ensure the stable operation of the power grid and the construction of smart grids. One of the most important components of the smart grid is various communication technologies. 5G network slicing is a typical application of the smart grid, because the wide-area distributed grid has greater requirements for low latency, high reliability and security. And 5G network slicing has the ability to meet its requirements. This paper analyzes the principle of 5G network slicing, analyzes the end-to-end isolation scheme of network slicing and the current smart grid slicing business model and existing problems, and proposes an effective solution for building a smart 5G slicing network.


Author(s):  
Xu xia ◽  
Lei Zhang ◽  
Chengli Mei ◽  
Jinyan Li ◽  
xuetian Zhu ◽  
...  

2021 ◽  
Vol 13 (10) ◽  
pp. 5334
Author(s):  
Zhi Ma ◽  
Songlin Sun

The development of 5G network slicing technology, combined with the application scenarios of vehicle–road collaborative positioning, provides end-to-end, large-bandwidth, low-latency, and highly reliable flexible customized services for Internet of Vehicle (IoV) services in different business scenarios. Starting from the needs of the network in the business scenario oriented to co-location, we researched the application of 5G network slicing technology in the vehicle–road cooperative localization system. We considered scheduling 5G slice resources. Creating slices to ensure the safety of the system, provided an optimized solution for the application of the vehicle–road coordinated positioning system. On this basis, this paper proposes a vehicle–road coordinated combined positioning method based on Beidou. On the basis of Beidou positioning and track estimation, using the advantages of the volumetric Kalman model, a combined positioning algorithm based on CKF was established. In order to further improve the positioning accuracy, vehicle characteristics could be extracted based on the traffic monitoring video stream to optimize the service-oriented positioning system. Considering that the vehicles in the urban traffic system can theoretically only travel on the road, the plan can be further optimized based on the road network information. It was preliminarily verified by simulation that this research idea has improved the relative single positioning method.


10.28945/4675 ◽  
2021 ◽  
Vol 16 ◽  
pp. 001-038
Author(s):  
Anshul Jain ◽  
Tanya Singh ◽  
Satyendra Kumar Sharma ◽  
Vikas Prajapati

Aim/Purpose: 5G and IoT are two path-breaking technologies, and they are like wall and climbers, where IoT as a climber is growing tremendously, taking the support of 5G as a wall. The main challenge that emerges here is to secure the ecosystem created by the collaboration of 5G and IoT, which consists of a network, users, endpoints, devices, and data. Other than underlying and hereditary security issues, they bring many Zero-day vulnerabilities, which always pose a risk. This paper proposes a security solution using network slicing, where each slice serves customers with different problems. Background: 5G and IoT are a combination of technology that will enhance the user experience and add many security issues to existing ones like DDoS, DoS. This paper aims to solve some of these problems by using network slicing and implementing an Intrusion Detection System to identify and isolate the compromised resources. Methodology: This paper proposes a 5G-IoT architecture using network slicing. Research here is an advancement to our previous implementation, a Python-based software divided into five different modules. This paper’s amplification includes induction of security using pattern matching intrusion detection methods and conducting tests in five different scenarios, with 1000 up to 5000 devices in different security modes. This enhancement in security helps differentiate and isolate attacks on IoT endpoints, base stations, and slices. Contribution: Network slicing is a known security technique; we have used it as a platform and developed a solution to host IoT devices with peculiar requirements and enhance their security by identifying intruders. This paper gives a different solution for implementing security while using slicing technology. Findings: The study entails and simulates how the IoT ecosystem can be variedly deployed on 5G networks using network slicing for different types of IoT devices and users. Simulation done in this research proves that the suggested architecture can be successfully implemented on IoT users with peculiar requirements in a network slicing environment. Recommendations for Practitioners: Practitioners can implement this solution in any live or production IoT environment to enhance security. This solution helps them get a cost-effective method for deploying IoT devices on a 5G network, which would otherwise have been an expensive technology to implement. Recommendation for Researchers: Researchers can enhance the simulations by amplifying the different types of IoT devices on varied hardware. They can even perform the simulation on a real network to unearth the actual impact. Impact on Society: This research provides an affordable and modest solution for securing the IoT ecosystem on a 5G network using network slicing technology, which will eventually benefit society as an end-user. This research can be of great assistance to all those working towards implementing security in IoT ecosystems. Future Research: All the configuration and slicing resources allocation done in this research was performed manually; it can be automated to improve accuracy and results. Our future direction will include machine learning techniques to make this application and intrusion detection more intelligent and advanced. This simulation can be combined and performed with smart network devices to obtain more varied results. A proof-of-concept system can be implemented on a real 5G network to amplify the concept further.


Sign in / Sign up

Export Citation Format

Share Document