The applications of instance-intensive workflow are widely used in e-commerce, advanced manufacturing, etc. However, existing studies normally do not consider the problem of reducing energy consumption by utilizing the characters of instance-intensive workflow applications. This paper presents a resource usage Prediction-based Energy-Aware scheduling algorithm, named PEA. Technically, this method improves the energy efficiency of instance-intensive cloud workflow by predicting resources utilization and the strategies of batch processing and load balancing. The efficiency and effectiveness of the proposed algorithm are validated by extensive experiments.
CITATION STYLE
Wang, Z., Wen, Y., Zhang, Y., Chen, J., & Cao, B. (2019). A resource usage prediction-based energy-aware scheduling algorithm for instance-intensive cloud workflows. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 268, pp. 626–642). Springer Verlag. https://doi.org/10.1007/978-3-030-12981-1_44
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