A scalable resource allocation scheme for NFV: Balancing utilization and path stretch

Network Function Virtualization (NFV) implements network middlebox functions in software, enabling them to be more flexible and dynamic. NFV resource allocation methods can exploit the capabilities of virtual- ization to dynamically instantiate network functions (NFs) to adapt to network conditions and demand. Deploying NFs requires decisions for both NF placement and routing of flows through these NFs in accordance with the required sequence of NFs that process each flow. The challenge in developing NFV resource allocation schemes is the need to manage the dependency between flow-level (routing) and network-level (placement) decisions. We model the NFV resource allocation problem as a multi-objective mixed integer linear programming problem, solving both flow-level and network-level decisions simultaneously. The optimal solution is capable of providing placement and routing decisions at a small scale. Based on the learnings from the optimal solution, we develop ClusPR, a heuristic solution that can scale to larger, more practical network environments supporting a larger number of flows. By elegantly capturing the dependency between flow routing and NF placement, ClusPR strikes a balance between minimizing path stretch and maximizing network utilization. Our experiments show ClusPR is capable of achieving near-optimal solution for a large sized network, in an acceptable time. Compared to state-of-the- art approaches, ClusPR is able to decrease the average normalized delay by a factor of 1.2–1.6× and the worst- case delay by 9–10×, with the same or slightly better network utilization.