Joint SFC Routing Update and Elastic Resource Configuration in Edge Cloud Environments

As key enabling technologies for 5G, edge computing pushes computing resources to the edge close to IoT users, enabling low-latency services. Meanwhile, network function virtualization abstracts complex services into service function chains (SFCs) consisting of multiple virtualized network functions (VNFs), significantly simplifying service management. However, the highly dynamic traffic in edge environments may cause the routing configurations of SFC requests and the resource configurations of VNFs to become outdated. The outdated configurations may result in VNF load imbalance or overload, severely disrupting service availability and degrading user quality of service (QoS). Therefore, this article studies the novel joint optimization of SFC routing update and elastic resource configuration problem, aiming to minimize the resource leasing cost of the service provider, while subject to multiresource capacity and update delay constraints. Considering all these characteristics, we formalize this problem as an integer linear programming and prove its NP-hardness. To tackle this problem, we propose a rounding-based routing update and resource configuration algorithm to find cost-effective routing paths and configuration types for requests and VNFs. Further, we design a backtracking-based greedy improvement algorithm that upgrades VNF resource configurations and adjusts request routing paths to accommodate more requests, thus boosting network throughput. Extensive simulation results show that compared with state-of-the-art solutions, our scheme can reduce the leasing cost by 17.8%, while improving network throughput and meeting user QoS.