Mobility-aware SFC migration in dynamic 5G-Edge networks

The fifth-generation mobile networks bring an evolution in the development of novel classes of applications, increasing the demand for performance and flexibility to support new classes of services. Edge Computing and Network Function Virtualization are two key technologies that bring data processing closer to the user and allow the replacement of traditional hardware-based network functions with virtualized counterparts, which reduces costs and permits the provision of low-latency services. In this scenario, services are often implemented as a Service Function Chain (SFC), consisting of a set of ordered Virtual Network Functions (VNFs) that provide the required service functionality. During service execution, users can move from one location to another, which impacts service performance. An approach to reduce the impact of user mobility is to migrate services as users move to different places. However, the SFC migration problem imposes several challenges that require complex decision-making. VNFs should be migrated to nodes that have the necessary resources to execute the VNF instances. Also, the migration should be fast and effective, using as few resources as possible to reduce migration costs. In this paper, we propose a proactive and iterative SFC migration strategy to address the performance impact caused by user mobility. Our proposed solution anticipates the movement of users and estimates the impact of their mobility on service delay, proactively triggering service migrations when needed. The proposed algorithm decides which VNFs of the SFC should be migrated and which compute nodes will host the migrating VNFs, fulfilling service, resource, and migration constraints while maintaining a low migration overhead. Our algorithm also considers the dynamic nature of the edge environment in which other SFC placement and migrations might be occurring when an SFC is being migrated, which also introduces new challenges related to the availability and concurrency of resources required for migration.