Provably Efficient Algorithms for Placement of Service Function Chains with Ordering Constraints

A Service Function Chain (SFC) is an ordered sequence of network functions, such as load balancing, content filtering, and firewall. With the Network Function Virtualization (NFV) paradigm, network functions can be deployed as pieces of software on generic hardware, leading to a flexibility of network service composition. Along with its benefits, NFV brings several challenges to network operators, such as the placement of virtual network functions. In this paper, we study the problem of how to optimally place the network functions within the network in order to satisfy all the SFC requirements of the flows. Our optimization task is to minimize the total deployment cost. We show that the problem can be seen as an instance of the Set Cover Problem, even in the case of ordered sequences of network functions. It allows us to propose two logarithmic factor approximation algorithms which have the best possible asymptotic factor. Further, we devise an optimal algorithm for tree topologies. Finally, we evaluate the performances of our proposed algorithms through extensive simulations. We demonstrate that near-optimal solutions can be found with our approach.

I. Introduction

Network Function Virtualization (NFV) is an emerging approach in which network functions are no longer executed by proprietary software appliances but instead, can run on generic-purpose servers located in small cloud nodes [1]. Examples of network functions include firewalls, load balancing, content filtering, and deep packet inspection. This technology aims at dealing with the major problems of today's enterprise middlebox infrastructure, such as cost, capacity rigidity, management complexity, and failures [2]. One of the main advantages of this approach is that Virtual Network Functions (VNFs) can be instantiated and scaled on demand without the need of installing new equipment.