Edge Cloud

Edge cloud computing aims to bring computation and data storage closer to end users, improving latency and bandwidth efficiency for applications like AI and IoT. Current research focuses on optimizing resource allocation and task offloading using techniques such as reinforcement learning, federated learning, and various neural network architectures to address challenges in heterogeneous environments and dynamic workloads. This approach is significant for enhancing the performance and scalability of various applications, particularly in areas like autonomous vehicles, smart mobility, and real-time data analytics, while also addressing privacy concerns through techniques like differential privacy.