Anzeige
Erschienen in:
2018 | OriginalPaper | Buchkapitel
Critical Task Scheduling for Data Stream Computing on Heterogeneous Clouds
verfasst von : Yen-Hsuan Kuo, Yi-Hsuan Lee, Kuo-Chan Huang, Kuan-Chou Lai
Erschienen in: Frontier Computing
Verlag: Springer Singapore
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Internet of Things is an emerging paradigm to enable easy data collection and exchange among a wide variety of devices. When the scale of Internet of Things enlarges, the cloud computing system could be applied to mine these big data generated by Internet of Things. This paper proposes a task scheduling approach for time-critical data streaming applications on heterogeneous clouds. The proposed approach takes the tasks in critical stages into consideration, and re-schedules these tasks to appropriate resources to shorten their processing time. In general, selecting the time-critical task to give more resources may remove the execution bottleneck. A small-scale cloud system including 3 servers is built for experiments. The performance of the proposed approach is evaluated by three micro-benchmarks. Preliminary experimental results demonstrate the performance improvement of the critical task scheduling approach.