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Vishakha Makode

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Open access Jun 2026

Intelligent Task Scheduling in Edge-Cloud Environments Using Double Deep Q-Network Reinforcement Learning

Experimental evaluation on a heterogeneous synthetic benchmark demonstrates that the proposed DDQN scheduler reduces SLA violations by approximately 85% relative to Round Robin and 72% relative to the greedy baseline, while achieving superior energy efficiency.

Vishakha Makode, Taresh Ayaspure · 0 citations