Optimization of the Hadoop ecosystem b ased on the dynamic trade-off model and SDAPC framework: cross-layer storage and computation synergy and trustworthy scheduling strategies

To address the core bottlenecks of high latency and low utilization in Hadoop ecosystem resource scheduling for the Zettabyte (ZB) era, this study proposes a cross-layer collaborative optimization method driven by a dynamic trade-off model. A SDAPC collaborative optimization framework integrating qu...

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Detalhes bibliográficos

Principais autores:	Ming Long, Hu Jianlong, Zhang Xinyi, Wang Yuxiang
Formato:	Artigo
Idioma:	Chinês
Publicado em:	China InfoCom Media Group 2026-01-01
coleção:	大数据
Assuntos:	Hadoop Ecosystem Ising Machine D-Wave Quantum Annealing Machine resource scheduling deep reinforcement learning
Acesso em linha:	http://www.j-bigdataresearch.com.cn/zh/article/doi/10.11959/j.issn.2096-0271.2026004/
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