On the Effective Parallelization and Near-Optimal Deployment of Service Function Chains

Abstract

Network operators compose Service Function Chains (SFCs) by tying different network functions (e.g., packet inspection, flow shaping, network address translation) together and process traffic flows in the order the network functions are chained. Leveraging the technique of Network Function Virtualization (NFV), each network function can be “virtualized” and decoupled from its dedicated hardware, and therefore can be deployed flexibly for better performance at any appropriate location of the underlying network infrastructure. However, an SFC often incurs high latency as traffic goes through the virtual network functions one after another. In this article, we first design an algorithm that leverages virtual network function dependency to convert an original SFC into a parallelized SFC (p-SFC). Then, to deploy multiple p-SFCs over the network for serving a large number of users, we model the deployment problem as an Integer Linear Program and propose a heuristic, ParaSFC, based on the Viterbi dynamic programming algorithm to estimate each p-SFC's occupation of the bottleneck resources and adjust the processing order of the p-SFCs in order to approximate the optimal solution. Finally, we conduct extensive trace-driven evaluations and exhibit that, compared to the Greedy method and the state-of-the-art CoordVNF method, ParaSFC reduces the average service latency of all the deployed p-SFCs by about 15 percent through parallelization while accommodating more SFC deployment requests over resource-limited networks.