Evolutionary Multiobjective Multicast Virtual Network Function Placement in NFV-SDN Networks

Abstract

Software-defined networking (SDN) and network functions virtualization (NFV) represent promising technologies for on-demand services that require the development of flexible multicast transmission mechanisms incorporating data processing functions at the network nodes.
The multicast routing problem in NFV-SDN networks aims to compute multicast routing trees and deploy virtual network functions (VNFs) to satisfy traffic demands while optimizing resource utilization and ensuring equitable data transmission. Due to the inherent computational complexity and the presence of conflicting objective functions, this paper formulates multicast routing and VNF placement as a multiobjective optimization problem (MOP), specifically minimizing the total resource cost and the maximum transmission delay variance.
Within this context, this study develops solutions based on Multi-objective Evolutionary Algorithms (MOEAs).
Simulations performed on test instances demonstrate the efficacy of the proposed methodologies, yielding efficient and non-dominated solutions when compared to a state-of-the-art single-objective approach.