Applying Fuzzy Logic to Efficiently Manage Shared Edge Infrastructure

Edge Computing promise a bright future for Internet of Things (IoT). Edge Computing servers can be geographically distributed to be closer to users and ensure low latency communications and real-time data processing for the third-party applications using this infrastructure. However, user mobility and limited Edge servers capabilities (CPU, memory, bandwidth) may cause many services placement failures. That's why in this article we propose a new strategy aimed at enabling a fair sharing of available Edge resources through a dynamic and real-time IoT Service placement. Our strategy uses Fuzzy Logic to enable 1) quick and low-cost deployment of the solution and 2) real-time modification of the policies defined by the Edge operator. It takes advantage, among others, of a microservice decomposition to optimize the use of the Edge architecture. Experiments demonstrate the benefits of our approach in terms of placement reliability, execution time and resources utilization.