Adaptive Policy-Driven Network Intelligence for Edge-to-Cloud Continuum

Edge-to-Cloud (E2C) is a rapidly emerging technology that aims to reduce overall traffic to the cloud by enabling Internet of Things (IoT) data processing as close to the data sources as possible, either on near- or far-edge devices. This paper introduces an adaptive, policy-driven framework for network intelligence designed to optimize E2C applications by intelligently enforcing network rules. By leveraging decentralized decision- making and Artificial Intelligence (AI) driven application profiling, the framework enables dynamic and adaptive network resource allocation, significantly enhancing network capacity, improving the capabilities between user applications and core network resources, and better correlating Quality of Service (QoS). The deployment of novel AI models, which leverage real-world monitoring data from E2C environments, demonstrates the framework's ability to enforce adaptive network policies and make informed decisions, contributing to more intelligent and resilient networks.