.png){kind=icon}
.png){kind=icon}
Return
Resource Allocation for Hybrid Quantum-Classical Communication Systems in Multiapplication-Enabled Power Grids
.png){kind=icon}
PRE
AI
DOI：10.1109/TII.2024.3452197.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Quantum communication is a promising technique for enhancing the information security. However, the limited availability of quantum keys due to low generation rates still remains a challenge in the quantum key distribution of power systems. To address this issue and optimize the utilization of quantum resources in the gradually developed quantum-secured power communication systems, this article proposes a hybrid resource optimization method by leveraging network virtualization technologies. First, we present a virtualized architecture using software-defined networking and network function virtualization to support multiapplication scenarios in power system communications. Subsequently, a two-stage resource optimization strategy is proposed to manage both classical and quantum resources. At the first stage, we design a network slicing scheme for allocating classical communication resources, such as channel capacity and time delay. This scheme aims to segregate information flows from applications with diversified quality of service requirements. At the second stage, encryption resources are allocated by matching limited quantum keys with communication requests with different priorities, thereby improving the overall performance of quantum-classical power communication systems. Finally, we construct a cosimulation testbed to validate the effectiveness of the proposed method through case studies.
Keywords:
Smart grids
Resource management
Virtualization
Security
Communication systems
Encryption
Computer architecture
Physical layer
Network slicing
Frequency control
Cybersecurity
multiapplication-enabled communication system
network virtualization
quantum communication
quantum key distribution (QKD)
resource allocation
Journal
IF:
9.9
Papers:
8.3K
Citations:
6.0W