To solve the loading and unloading problems of RMG (Rail Mounted Gantry), quay crane and AGV (Automated Guided Vehicle), this paper proposes a hierarchical cooperative scheduling algorithm. Firstly, the operation task...
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To further improve the efficiency and performance of cloud computing task scheduling and cope with the diversity of user tasks, the study unfolds the construction of cloud computing task scheduling model based on heur...
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In this paper, we investigate the issues of real-time sensor scheduling and state estimator design within large-scale sensor network systems. Specifically, data redundancy sometimes occurs in large-scale sensor arrays...
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Earth observation satellites play a pivotal role in advancing our understanding of the Earth and its environment. By strategically scheduling satellite orbits and observation, they perform a wide range of critical tas...
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To address the randomness and volatility of renewable energy generation technologies, we propose an online scheduling strategy for renewable energy power systems based on a digital twin (DT) model. By constructing a d...
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This paper proposes new joint flow control and link scheduling (JFCLS) algorithms for the classical network utility maximization (NUM) problem with unknown utility functions. Our algorithm leverages the idea of optimi...
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The fact that various jobs have different quality standards is a major problem with scheduling algorithms. Only a small number of algorithms are created to satisfy these various demands. For multivariate situations, n...
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This paper introduces a novel CPU scheduling algorithm for uniprocessor systems that employs a probabilistic function to enhance fair resource allocation. Unlike traditional algorithms, our approach specifically tackl...
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The network has become a bottleneck for generative artificial intelligence (GAI) jobs. Accelerating GAI jobs in edge data centers using hybrid electrical/optical switch is considered a promising solution. This archite...
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The network has become a bottleneck for generative artificial intelligence (GAI) jobs. Accelerating GAI jobs in edge data centers using hybrid electrical/optical switch is considered a promising solution. This architecture optimizes bandwidth utilization by enabling demand-aware topology reconfiguration through flexible configuration of optical circuit switche optical circuit switches (OCS). However, frequent topology reconfiguration may increase latency. Therefore, there is a balanced relationship between latency and bandwidth utilization. In this article, we propose a multigranularity adaptive interleaved algorithm for service scheduling in edge data centers. First, different degrees of time slot shifts are introduced based on the latency sensitivity of jobs, where large bandwidth GAI jobs are transmitted in a single hop by configuring a demand-aware topology. Additionally, when the reconfiguration threshold is met, low-priority ports are prioritized for reconfiguration to ensure latency requirements are met. This approach effectively resolves the tradeoff between bandwidth utilization and latency by decoupling them from each other. Simulation results show that this approach can effectively reduce the latency and improve the network throughput.
Controlling fluid levels in cone-shaped discharge tanks can be challenging, especially in the chemical industry. This paper presents a novel approach for achieving precise level control in such tanks using a proportio...
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