Energy-Aware Service Function Chaining Embedding in NFV Networks

Network function virtualization (NFV) is a new networking paradigm based on decoupling network functions from dedicated hardware, so these network functions can be run as pieces of software on general-purpose computation servers, which are called virtual network functions. In addition to guarantee the service qualities provided by NFV networks comparable to those provided by traditional telecommunication networks, energy consumption becomes one of the challenges faced by NFV. This is due to a large number of general computation servers that consume a significant amount of energy. We address here the problem of how to provide an energy-aware service function chaining (SFC) embedding in NFV networks with a hierarchical resource allocation, where an SFC has a set of virtual network functions to be executed in a specific sequential order providing a specific network service. Assuming a dynamic traffic scenario, we introduce for this new problem an integer linear programming (ILP) and three polynomial heuristic algorithms for resource allocation. All three heuristic algorithms achieve energy savings by shutting down idle devices and balance the tradeoff between energy cost and SFC request acceptance ratio. Numerical results demonstrate the quality of the proposed heuristic algorithms in terms of acceptance ratio by comparing them with the ILP method and a method extended from an exiting algorithm despite the fact that they save energy.

Automated summary

Network function virtualization (NFV) is a new networking paradigm that decouples network functions from dedicated hardware, allowing them to run on general-purpose computation servers as virtual network functions. However, energy consumption poses a challenge for NFV networks due to the significant amount of energy consumed by general computation servers. In this study, we address the problem of energy-aware service function chaining (SFC) embedding in NFV networks with hierarchical resource allocation. We propose integer linear programming (ILP) and three polynomial heuristic algorithms for resource allocation, which achieve energy savings without compromising the SFC request acceptance ratio when compared to existing methods.