A Kepler scientific workflow to facilitate and standardize marine monitoring sensor parsing and dynamic adaption

Li, Xiu; Song, Jingdong; Huang, Rongsheng

doi:10.1109/icsess.2014.6933739

Cited by 1 publication

(1 citation statement)

References 4 publications

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“…Kepler as shown in Fig. 1 provides an intuitive graphical user interface to design and present workflows in the work area called canvas, and scientists can just simply drag and drop the specific modules into the canvas to create their own executable scientific workflows which make scientists or others with little background in computer science can understand the execution of a workflow easily [18]. Taverna is also an open-source SWfMS that is mainly used in biology and bioinformatics.…”

Section: Various Swfmssmentioning

confidence: 99%

A scientific workflow management system architecture and its scheduling based on cloud service platform for manufacturing big data analytics

Song

Huang

2015

Int J Adv Manuf Technol

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To improve the efficiency and productivity of modern manufacturing, the requirements for enterprises are discussed. The new emerged technologies such as cloud computing and internet of things are analyzed and the bottlenecks faced by enterprises in manufacturing big data analytics are investigated. Scientific workflow technology as a method to solve the problems is introduced and an architecture of scientific workflow management system based on cloud manufacturing service platform is proposed. The functions of each layer in the architecture are described in detail and implemented with an existing workflow system as a case study. The workflow scheduling algorithm is the key issue of management system, and the related work is reviewed. This paper takes the general problems of existing algorithms as the motivation to propose a novel scheduling algorithm called MP (max percentages) algorithm. The simulation results indicate that the proposed algorithm has performed better than the other five classic algorithms with respect to both the total completion time and load balancing level.

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Section: Various Swfmssmentioning

confidence: 99%