TY - GEN
T1 - Resource-Aware Intent Compilation for Virtual Private Cloud
AU - Zhang, Jia
AU - Cao, Wanyue
AU - Fu, Qiang
AU - Li, Hao
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Migrating enterprise IT services to the cloud is becoming a trend. However, configuring virtual networks in the cloud is a costly and error-prone task. In this paper, we model the problem of VPC intent compilation and prove that the problem is NP-hard. We design a heuristic method to automatically translate the intents into VPC configurations. To facilitate the heuristic, we propose an algorithm for finding small cuts (AFSC) based on the Louvain algorithm, which is used to separate subnets across VPCs. The generated configurations find an equilibrium between maximizing the network performance and minimizing the resource consumption. Experimental results show that our heuristic method reaches 100% correctness, compiles large intent sets from real-world networks with hundreds of subnets and thousands of intents in under a minute, and improves the effectiveness by ∼2.8× in terms of resource consumption relative to network performance.
AB - Migrating enterprise IT services to the cloud is becoming a trend. However, configuring virtual networks in the cloud is a costly and error-prone task. In this paper, we model the problem of VPC intent compilation and prove that the problem is NP-hard. We design a heuristic method to automatically translate the intents into VPC configurations. To facilitate the heuristic, we propose an algorithm for finding small cuts (AFSC) based on the Louvain algorithm, which is used to separate subnets across VPCs. The generated configurations find an equilibrium between maximizing the network performance and minimizing the resource consumption. Experimental results show that our heuristic method reaches 100% correctness, compiles large intent sets from real-world networks with hundreds of subnets and thousands of intents in under a minute, and improves the effectiveness by ∼2.8× in terms of resource consumption relative to network performance.
UR - https://www.scopus.com/pages/publications/85209187785
U2 - 10.1109/ISCC61673.2024.10733611
DO - 10.1109/ISCC61673.2024.10733611
M3 - 会议稿件
AN - SCOPUS:85209187785
T3 - Proceedings - IEEE Symposium on Computers and Communications
BT - 2024 IEEE Symposium on Computers and Communications, ISCC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 29th IEEE Symposium on Computers and Communications, ISCC 2024
Y2 - 26 June 2024 through 29 June 2024
ER -