Multi objective reinforcement learning driven task offloading algorithm for satellite edge computing networks

Nature·Jul 5

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Research has been conducted on task offloading algorithms for satellite edge computing networks, utilizing multi-objective reinforcement learning. Various studies have explored the application of reinforcement learning in different computing environments, including mobile edge, cloud, fog, and edge-cloud systems, with a focus on energy efficiency, cost optimization, and security. The approaches and frameworks developed include customized deep Q-networks, neuro-fuzzy reinforcement learning, and quantum-driven schedulers, aiming to improve task scheduling and offloading in these systems.

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