Abstract
Network Function Virtualization (NFV) can support customized on- demand network services with flexibility and cost-efficiency. Virtual Network Function (VNF) instances need to be scaled out, scaled in, and reallocated across the NFV infrastructure (NFVI) to avoid a violation of service agreements when the demand traffic changes. However, selecting the new placement of VNFs for migrating a service function chain (SFC) is an issue of efficient NFV control. We propose two novel integer linear programming (ILP) models and two approximation algorithms for SFC placement and migration to maximize the cost-efficiency of an NFV network regarding the changes of service demands and dynamic routing. The ILP models allow us to obtain the optimal solutions of SFC placement and migration with explicit dynamic paths. The approximation migration results provided by our proposed heuristic and reinforcement learning algorithms are close to the optimal solution. Evaluation results carried out with real datasets and synthetic network topologies provide a helpful suggestion of a migration strategy for an NFV service provider to optimize the operating cost of an NFV network in the long term.
Highlights
The 6G network will support customized on-demand network services, which require a flexible network architecture
The challenging questions are the following: What is the optimal migration of service function chain (SFC) when the volume of demand traffic changes? When considering the dynamic routing, what is an explicit path of SFC on NFV infrastructure (NFVI) in the optimal migration? What is the size of an Network Function Virtualization (NFV) network in which we can find the optimal SFC migration solution with acceptable computation time? What efficient approximation algorithm can quickly react to the demand changes in an extensive NFV network? We address those issues as a vital component of a dynamic NFV network
EVALUATION We evaluate the performance of our proposed solution approaches, including FPO, FMO, FMH, and FMR for SFC migration with explicit paths in NFV
Summary
The 6G network will support customized on-demand network services, which require a flexible network architecture. When the volume of demand traffic changes, some nodes in NFVI are possibly overloaded, leading to a quality of services (QoS) violation. It is crucial to optimize SFC migration for enabling customized on-demand network services with flexibility and cost-efficiency in the 6G network. Most previous work assumes a set of pre-computed paths and does not produce an explicit SFC routing path on a physical NFV infrastructure, which leads to a suboptimal solution. Our work is designed to fill the gap by considering explicit dynamic routing paths when finding the optimal migration solution. Our work aims to optimize SFC migration, considering both the new placement of VNF and explicit paths of SFC to maximize cost-efficiency under available system resources. When considering the dynamic routing, what is an explicit path of SFC on NFVI in the optimal migration?
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