Toward Optimal Hybrid Service Function Chain Embedding in Multiaccess Edge Computing

The emerging multiaccess edge computing (MEC) architecture brings the needed computing resource to the network edge. Many 5G and Internet of Things (IoT) applications are latency sensitive and computation intensive in MEC systems. To flexibly provide and manage the network service requests in MEC systems, network function virtualization (NFV) can be employed to create a chain of service functions (SFs), namely, SF chain (SFC). Through SFC, the customer forwards user data to the edge server/cloud, and the edge server/cloud may return the processed results/models to the customer. When the forward and backward traffic is carrying different content, different SFs may be required for the forward and backward traffic, which requires a hybrid SFC (h-SFC). In this article, we study how to minimize the latency cost when embedding an h-SFC in MEC systems. We define a new problem called minimum latency hybrid SFC embedding (ML-HSFCE) and propose an algorithm, namely, optimal hybrid SFC embedding (Opt-HSFCE) to optimally embed a given h-SFC in MEC systems. Our extensive simulations and analysis show that the proposed Opt-HSFCE needs much less runtime compared with the brutal force algorithm and significantly outperforms the schemes that are directly extended from the existing techniques.