Dynamic multi objective task scheduling in cloud computing using reinforcement learning for energy and cost optimization. [PDF]
Yu X, Mi J, Tang L, Long L, Qin X.
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An Effective QoS-Aware Hybrid Optimization Approach for Workflow Scheduling in Cloud Computing. [PDF]
Cui M, Wang Y.
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Toward intelligent IoT scheduling with quantum-inspired latent models for energy and latency optimization. [PDF]
Alyas T +6 more
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Efficient workflow scheduling using an improved multi-objective memetic algorithm in cloud-edge-end collaborative framework. [PDF]
Cui G, Zhang W, Xu W, Bao H.
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Smart load balancing in cloud computing: Integrating feature selection with advanced deep learning models. [PDF]
Sanjalawe Y +5 more
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Energy-conscious scheduling in edge environments: hybridization of traditional control and DE algorithm. [PDF]
Ma K, Xu L.
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A hybrid evolution strategies algorithm for non-permutation flow shop scheduling problems. [PDF]
Khurshid B +4 more
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DE-RALBA: dynamic enhanced resource aware load balancing algorithm for cloud computing. [PDF]
Hussain A +3 more
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Dynamic task allocation in fog computing using enhanced fuzzy logic approaches. [PDF]
Jin W, Rezaeipanah A.
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An improved scatter search algorithm for solving job shop scheduling problems with parallel batch processing machine. [PDF]
Wang H, Xiong H, Zuo W, Shi S.
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