An efficient linear programming rounding-and-refinement algorithm for large-scale network slicing problem

TL;DR

This paper introduces a polynomial-time, two-stage LP-based algorithm for large-scale network slicing that efficiently maps virtual network requests to shared infrastructure while satisfying service constraints.

Contribution

It presents a novel LP rounding-and-refinement algorithm that improves solution quality and computational efficiency for the NP-hard network slicing problem.

Findings

Achieves better trade-off between solution quality and complexity

Polynomial worst-case complexity makes it suitable for large-scale problems

Numerical results demonstrate effectiveness and efficiency

Abstract

In this paper, we consider the network slicing problem which attempts to map multiple customized virtual network requests (also called services) to a common shared network infrastructure and allocate network resources to meet diverse service requirements, and propose an efficient two-stage algorithm for solving this NP-hard problem. In the first stage, the proposed algorithm uses an iterative linear programming (LP) rounding procedure to place the virtual network functions of all services into cloud nodes while taking traffic routing of all services into consideration; in the second stage, the proposed algorithm uses an iterative LP refinement procedure to obtain a solution for traffic routing of all services with their end-to-end delay constraints being satisfied. Compared with the existing algorithms which either have an exponential complexity or return a low-quality solution, our proposed algorithm achieves a better trade-off between solution quality and computational complexity. In particular, the worst-case complexity of our proposed algorithm is polynomial, which makes it suitable for solving large-scale problems. Numerical results demonstrate the effectiveness and efficiency of our proposed algorithm.