Microservice Offloading

Microservice offloading optimizes the execution of small, independent services by strategically assigning them to either local devices or remote edge servers. Current research heavily focuses on developing intelligent offloading strategies, often employing reinforcement learning algorithms, sometimes enhanced by digital twin modeling to predict and adapt to dynamic network conditions and resource availability. This research aims to improve efficiency, reduce latency, and minimize resource consumption in collaborative edge computing environments, impacting the performance and scalability of cloud-based and edge-deployed applications.