Performance-aware placement and chaining scheme for virtualized network functions: a particle swarm optimization approach
This work addresses a specific bottleneck in network functions virtualization (NFV) for network providers by providing an integrated solution, though it is incremental as it builds on existing PSO methods.
The paper tackles the integrated placement and chaining problem for virtualized network functions (VNFs) by formulating it as an optimization problem and solving it with a particle swarm optimization (PSO) approach, resulting in feasible and high-quality solutions that minimize server usage, propagation delay, and link utilization.
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.