Focal Interest
Focal Interest

IoT and Edge/Fog Computing

External reference: https://openalex.org/T10273

  1. Proactive VM consolidation cuts energy use and SLA violations
    Framework for VM consolidation combining workload prediction and physics-constrained reinforcement learning. Achieves 23.2% energy reduction and 43.5% SLA violation reduction in cloud datacenters.
  2. Hybrid deep learning improved edge-cloud task scheduling in simulation
    Deep reinforcement learning framework for adaptive task scheduling in edge-cloud computing with improved SLA compliance, reduced operational costs, and lower task rejection rates.
  3. AGENT improved makespan in heterogeneous cloud task allocation
    AGENT framework improves task allocation in cloud systems using elitism-guided genetic algorithm with adaptive parameters, achieving 3-29% makespan improvements for heterogeneous VM scheduling.