A Near Optimal Reliable Orchestration Approach for Geo-Distributed Latency-Sensitive SFCs

Traditionally, Network Function Virtualization uses Service Function Chaining (SFC) to place service functions and chain them with corresponding flows allocation. With the advent of Edge computing and IoT, a reliable orchestration of latency-sensitive SFCs is needed to compose and maintain them in geo-distributed cloud infrastructures. However, the optimal SFC composition in this case becomes the NP-hard integer multi-commodity-chain flow (MCCF) problem that has no known approximation guarantees. In this paper, we first outline our novel practical and near optimal SFC composition scheme which is based on our novel metapath composite variable approach, admits end-to-end network QoS constraints (e.g., latency) and reaches 99% optimality on average in seconds for practically sized geo-distributed cloud infrastructures. We then propose a novel metapath-based SFC maintenance algorithm that guarantees a distributed control plane consistency without use of expensive consensus protocols. Using trace-driven simulations comprising of challenging disaster-incident conditions, we show that our solution composes twice as many SFCs and uses $\sim$10x less control messages than state-of-the-art methods. Finally, experimental evaluations of our SFC orchestration prototype deployed on a realistic cloud/edge computing testbed show significant speed-ups (up to 3.5x) for our case-study geo-distributed latency-sensitive object tracking pipeline w.r.t. its IP-based cloud computing alternative.