Intelligent Green Resource Management for Blockchain‐Powered IoT Networks Through Deep Reinforcement Learning

ABSTRACT Integrating blockchain technology with Internet of Things (IoT) networks presents opportunities and challenges for sustainable computing. While blockchain ensures secure and transparent data management, its energy‐intensive nature poses significant environmental concerns, particularly in resource‐constrained IoT environments. This paper proposes SERO‐DRL, a novel deep reinforcement learning approach for energy‐efficient resource optimization in blockchain‐enabled sustainable IoT networks. We develop a comprehensive framework that jointly optimizes computational offloading and resource allocation while considering renewable energy availability and environmental impact. The framework includes an innovative reward mechanism that incentivizes energy‐efficient behavior while ensuring fair resource allocation among IoT devices. Experimental results demonstrate SERO‐DRL's superior performance, achieving an 18.5% reduction in total system costs and a 40% decrease in environmental impact compared to baseline approaches.