Optimized Spatiotemporal Data Scheduling Based on Maximum Flow for Multilevel Visualization Tasks

Massive spatiotemporal data scheduling in a cloud environment play a significant role in real-time visualization. Existing methods focus on preloading, prefetching, multithread processing and multilevel cache collaboration, which waste hardware resources and cannot fully meet the different schedulin...

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Vydané v:	ISPRS international journal of geo-information Ročník 9; číslo 9; s. 518
Hlavní autori:	Zhu, Qing, Chen, Meite, Feng, Bin, Zhou, Yan, Li, Maosu, Xu, Zhaowen, Ding, Yulin, Liu, Mingwei, Wang, Wei, Xie, Xiao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.09.2020
Predmet:	Adaptive algorithms Algorithms Caching Cloud computing cloud environment Computer simulation Data Data processing Efficiency Electronic data processing environment flow Global optimization Hardware Mathematical optimization Maximum flow methodology Methods Multilevel multilevel visualization tasks Optimization Priority scheduling Resources Scheduling Scheduling (Management) scheduling optimization Software spatial data Spatiotemporal data Task scheduling topology Visualization Visualization (Computers) wastes China
ISSN:	2220-9964, 2220-9964
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