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EdgeGuard-AI: Zero-Trust and Load-Aware Federated Scheduling for Secure and Low-Latency IoT Edge Networks. [PDF]
Alanazi AG, Alanazi HA.
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A human microfluidic blood‐brain barrier (mBBB) model enables spatially resolved comparison of nanoparticle trafficking. Extracellular vesicles (EVs), liposomes, and nanoplastics exhibit distinct transport and disruption behaviors, revealing that membrane composition and uptake pathways govern BBB interaction.
Bryan B. Nguyen +9 more
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IntelliScheduler: an edge-cloud computing environment hybrid deep learning framework for task scheduling based on learning. [PDF]
Raju LR +5 more
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Edge computing task scheduling mechanism based on multi-dimensional feature extraction and attention fusion. [PDF]
Zhang S, Li JY, Yu P.
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Optimizing sleep scheduling in wireless sensor networks via node utility and critical target prioritization. [PDF]
Wu J, Tian S, Qi X, Cai Z, Wang P.
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Research on online EDI order scheduling optimization strategy in manufacturing enterprises based on time-varying Markov chains. [PDF]
Wulan Q.
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Parallel Scheduling Algorithms
Operations Research, 1983Parallel algorithms are given for scheduling problems such as scheduling to minimize the number of tardy jobs, job sequencing with deadlines, scheduling to minimize earliness and tardiness penalties, channel assignment, and minimizing the mean finish time. The shared memory model of parallel computers is used to obtain fast algorithms.
Dekel, Eliezer, Sahni, Sartaj
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On Manpower Scheduling Algorithms
SIAM Review, 1982This paper provides a systematic review of several of the available manpower scheduling algorithms from a common framework. The five-stage framework is based on the recognition that the general scheduling problem can be decomposed into five separate but related subproblems or stages, namely, the determination of temporal manpower requirements, total ...
Tien, James M., Kamiyama, Angelica
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