Incremental Server Deployment for Software-Defined NFV-Enabled Networks

Network Function Virtualization (NFV) is a new paradigm to enable service innovation through virtualizing traditional network functions. To construct a new NFV-enabled network, there are two critical requirements: minimizing server deployment cost and satisfying switch resource constraints. However, prior work mostly focuses on the server deployment cost, while ignoring the switch resource constraints (e.g., switch's flow-table size). It thus results in a large number of rules on switches and leads to massive control overhead. To address this challenge, we propose an incremental server deployment (INSD) problem for construction of scalable NFV-enabled networks. We prove that the INSD problem is NP-Hard, and there is no polynomial-time algorithm with approximation ratio of (1- epsilon) center dot lnm, where epsilon is an arbitrarily small value and m is the number of requests in the network. We then present an efficient algorithm with an approximation ratio of 2 center dot H(q center dot p), where q is the number of VNF's categories and p is the maximum number of requests through a switch. We evaluate the performance of our algorithm with experiments on physical platform (Pica8), Open vSwitches, and large-scale simulations. Both experimental results and simulation results show high scalability of the proposed algorithm. For example, our solution can reduce the control and rule overhead by about 88% with about 5% additional server deployment, compared with the existing solutions.