Delay-Aware Service Function Chain Embedding and Scheduling in Edge Clouds

Abstract

Edge Computing (EC) provides low-latency environment for delay-sensitive network services by deploying limited cloud infrastructure at the edge of the network. Network Function Virtualization (NFV) further enhances flexibility by replacing hardware with Virtual Network Functions (VNFs) that can run on general servers. In NFV, Service Function Chaining (SFC) can provide network services by combining several VNFs in a chain or graph format. NFV therefore allows to deploy network functions in a more flexible and cost-efficient manner, and schedule network resources according to the dynamical variation of network traffic in EC. Optimizing SFC embedding and performance is crucial for service providers to reduce costs and maximize benefits. This paper investigates dynamic SFC embedding in geo-distributed edge clouds for requests with diverse delay requirements. We propose SFCES, a framework integrating a cost-efficient embedding (SFC-CEB) algorithm with a request rerouting (RR) algorithm. SFC-CEB handles initial embedding based on delay needs, while RR periodically re-optimizes routing for active requests. Experimental results show that SFCES reduces embedding cost by <inline-formula><tex-math notation="LaTeX">$46\% \sim 64\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>46</mml:mn><mml:mo>%</mml:mo><mml:mo>∼</mml:mo><mml:mn>64</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="wang-ieq1-3735294.gif"/></alternatives></inline-formula> compared to state-of-the-art schemes like RDIP.