Proactive Service Orchestration with Deadline

Abstract

In network function virtualization, network services are implemented as service function chains (SFCs). An extensive body of work exists on SFC orchestration, although a vast majority of them consider reactive algorithms that reprovision resources in response to service demand fluctuations. As such, they result in unpredictable and often significant delays that negatively affect the performance of delay-sensitive SFCs. In this paper, we consider proactive SFC orchestration and develop exact and approximate algorithms that perform well under general service demands without requiring frequent resource reprovisioning. Specifically, we first formulate SFC orchestration with deadline as a mixed integer non-linear program and show that it can be reduced to a second-order cone program, which can be solved using standard optimization software, albeit for small problem instances. We then design an approximate algorithm for large problem instances by applying iterative rounding and variable fixing techniques to the exact problem formulation. We present extensive model-driven simulation results to study the behavior of our algorithms in small and large problem instances and demonstrate their ability to achieve any desired provisioning-reprovisioning trade-off. We further compare the performance of our approximate algorithm against two recently proposed algorithms called FFCA and MaxZ.