Performance-aware placement and chaining scheme for virtualized network functions: a particle swarm optimization approach

TL;DR

This paper presents a particle swarm optimization-based scheme for the integrated placement and chaining of virtualized network functions, aiming to optimize resource utilization and network performance.

Contribution

It introduces a novel PSO-based approach that jointly considers VNF placement and chaining, addressing gaps in existing methods that treat these problems separately.

Findings

The proposed algorithm finds feasible, high-quality solutions.

It effectively minimizes server usage, delay, and link utilization.

The approach outperforms some existing methods in simulation results.

Abstract

Network functions virtualization (NFV) is a new concept that has received the attention of both researchers and network providers. NFV decouples network functions from specialized hardware devices and virtualizes these network functions as software instances called virtualized network functions (VNFs). NFV leads to various benefits, including more flexibility, high resource utilization, and easy upgrades and maintenances. Despite recent works in this field, placement and chaining of VNFs need more attention. More specifically, some of the existing works have considered only the placement of VNFs and ignored the chaining part. So, they have not provided an integrated view of host or bandwidth resources and propagation delay of paths. In this paper, we solve the VNF placement and chaining problem as an optimization problem based on the particle swarm optimization (PSO) algorithm. Our goal is to minimize the required number of used servers, the average propagation delay of paths, and the average utilization of links while meeting network demands and constraints. Based on the obtained results, the algorithm proposed in this study can find feasible and high-quality solutions.