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Quantum-Assisted Joint Virtual Network Function Deployment and Maximum Flow Routing for Space Information Networks

Yu Zhang, Yanmin Gong, Lei Fan, Yu Wang, Zhu Han, Yuanxiong Guo

TL;DR

This paper proposes a hybrid quantum-classical Benders’ decomposition (HQCBD) algorithm, which converts the master problem of the Benders’ decomposition into the quadratic unconstrained binary optimization (QUBO) model and solve it with quantum computers.

Abstract

Network function virtualization (NFV)-enabled space information network (SIN) has emerged as a promising method to facilitate global coverage and seamless service. This paper proposes a novel NFV-enabled SIN to provide end-to-end communication and computation services for ground users. Based on the multi-functional time expanded graph (MF-TEG), we jointly optimize the user association, virtual network function (VNF) deployment, and flow routing strategy (U-VNF-R) to maximize the total processed data received by users. The original problem is a mixed-integer linear program (MILP) that is intractable for classical computers. Inspired by quantum computing techniques, we propose a hybrid quantum-classical Benders' decomposition (HQCBD) algorithm. Specifically, we convert the master problem of the Benders' decomposition into the quadratic unconstrained binary optimization (QUBO) model and solve it with quantum computers. To further accelerate the optimization, we also design a multi-cut strategy based on the quantum advantages in parallel computing. Numerical results demonstrate the effectiveness and efficiency of the proposed algorithm and U-VNF-R scheme.

Quantum-Assisted Joint Virtual Network Function Deployment and Maximum Flow Routing for Space Information Networks

TL;DR

This paper proposes a hybrid quantum-classical Benders’ decomposition (HQCBD) algorithm, which converts the master problem of the Benders’ decomposition into the quadratic unconstrained binary optimization (QUBO) model and solve it with quantum computers.

Abstract

Network function virtualization (NFV)-enabled space information network (SIN) has emerged as a promising method to facilitate global coverage and seamless service. This paper proposes a novel NFV-enabled SIN to provide end-to-end communication and computation services for ground users. Based on the multi-functional time expanded graph (MF-TEG), we jointly optimize the user association, virtual network function (VNF) deployment, and flow routing strategy (U-VNF-R) to maximize the total processed data received by users. The original problem is a mixed-integer linear program (MILP) that is intractable for classical computers. Inspired by quantum computing techniques, we propose a hybrid quantum-classical Benders' decomposition (HQCBD) algorithm. Specifically, we convert the master problem of the Benders' decomposition into the quadratic unconstrained binary optimization (QUBO) model and solve it with quantum computers. To further accelerate the optimization, we also design a multi-cut strategy based on the quantum advantages in parallel computing. Numerical results demonstrate the effectiveness and efficiency of the proposed algorithm and U-VNF-R scheme.
Paper Structure (26 sections, 40 equations, 10 figures, 3 tables, 2 algorithms)

This paper contains 26 sections, 40 equations, 10 figures, 3 tables, 2 algorithms.

Figures (10)

  • Figure 1: An example of the SFC with three functions in the SIN.
  • Figure 2: Schematic of decoupling a function node into three types of components: virtual sub-node, virtual function nodes, and virtual transmission links.
  • Figure 3: MF-TEG for an example NFV-enabled SIN with three-time slots.
  • Figure 4: An overview of (a) Single-Cut HQCBD and (b) Multi-Cut HQCBD.
  • Figure 5: Convergence performance of different HQCBD strategies compared to the classical BD approach for solving problem $\textbf{P}_1$ ($L=4, B_{i,j}=30MHz, C(v_i^t, v_i^{t+1})=50Mbit, C_i^t=1500Mbit/s$).
  • ...and 5 more figures