Deft Scheduling of Dynamic Cloud Workflows with Varying Deadlines via Mixture-of-Experts

arXiv:2606.01162 · cs.AI · Submitted 2026-05-31 · Read on arXiv

cs.AI

Submitted: 2026-05-31

Updated: 2026-06-02

Code: https://github.com/yashenCS/DEFT

Terminology

• Embeddings — 15× in this paper · explained in 2 episodes
• Reinforcement Learning — 13× in this paper · explained in 4 episodes
• Ablation — 10× in this paper · explained in 1 episode
• Deep Reinforcement Learning — 7× in this paper · explained in 2 episodes
• Generalization — 6× in this paper · explained in 13 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Action Space — 3× in this paper · explained in 1 episode
• Adaptability — 3× in this paper · explained in 1 episode
• Attention Mechanism — 3× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Cost-Aware Dynamic Workflow Scheduling — 3× in this paper
• Mixture of Experts — 3× in this paper · explained in 2 episodes
• Redundancy — 3× in this paper · explained in 2 episodes
• State Embedding Module — 3× in this paper
• Core — 2× in this paper · explained in 2 episodes
• Cross-Attention Mechanism — 2× in this paper · explained in 2 episodes
• Deep Reinforcement Learning (DRL) — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• GNNs — 2× in this paper · explained in 2 episodes
• Markov Decision Process — 2× in this paper
• Markov Decision Process (MDP) — 2× in this paper · explained in 10 episodes
• Mixture-of-Experts (MoE) — 2× in this paper · explained in 7 episodes
• Priority Mapping Module — 2× in this paper
• Sparsity — 2× in this paper · explained in 4 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptivity — 1× in this paper · explained in 1 episode
• Combinatorial Optimization — 1× in this paper · explained in 2 episodes
• Explainability — 1× in this paper · explained in 3 episodes
• Feed-Forward Network — 1× in this paper
• Reward Function — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes

Sources

• SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity and Hierarchy
• Evolution Strategies as a Scalable Alternative to Reinforcement Learning
• Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
• Graph Attention Networks
• MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts

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