Task Offloading

Task offloading optimizes resource utilization by distributing computational tasks from resource-constrained devices (e.g., mobile phones, IoT devices, UAVs) to more powerful entities (e.g., edge servers, cloud servers, other devices). Current research heavily employs reinforcement learning (RL), often in multi-agent settings, coupled with graph neural networks (GNNs) and deep learning models to dynamically allocate resources and make offloading decisions, addressing challenges like latency, energy consumption, and network congestion. This field is crucial for enabling efficient and scalable operation of increasingly complex systems in diverse applications, including autonomous driving, mobile edge computing, and the Internet of Things.