Abstract

Edge computing is a novel computing paradigm moving server resources closer to end-devices. It helps unleashing the full potential of high-performance access networks with respect to ultra-low latency and transfer rate and improve resilience to problems at core networks and data centers. Multi-access Edge Computing (MEC), is a standard solution by European Telecommunications Standards Institute (ETSI) for access network-level edge computing. MEC, operating at access network level, is an ideal solution for the most cases. However, there are still some challenges to address: first is related to the vulnerability to access network problems and the second is about the high load inflicted to access networks and MEC servers. This is a particular issue in massive-scale Internet of Things (IoT) use cases, where numerous sensors may produce high amounts of data, or where critical system functionalities must be ensured also during access network problems. In this paper, we study the feasibility of bringing some edge functions to the local level as virtualized and dynamically deployable components utilizing local hardware capacity. For the study, we have implemented a local edge networking prototype based on local microservices, called nanoservices, implemented using Docker containers and deployed using Docker Swarm-based orchestration. Since IoT networks typically consist of constrained-capacity devices, our focus is in optimizing the resources of the proposed nanoservices.