Workflow management system based on WEB technology

Qi, Lixia

doi:10.1007/s10586-017-0786-7

Cited by 5 publications

(1 citation statement)

References 8 publications

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“…Among these applications, workflow is one the most important types especially when plenty of as computational devices, data, applications, and scientific instruments are involved and need to be orchestrated (Wu et al, 2015;Xiao and Hao, 2016;Casas et al, 2017). Imposing the workflow paradigm for application composition offers several advantages, including orchestrated resource sharing, optimised resource utilisation, automatic data processing, inter-organisational collaboration and so on (Zhao et al, 2015;Qi, 2017). Therefore, scientific communities, such as high-energy physics, bioinformatics, geophysics, etc., have widely applied workflow to perform complex simulations or process large volumes of datasets (Le-Blanc et al, 2013;Krieger et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

CWOM: a lightweight cloud-oriented workflow optimisation middleware

Xiao

2021

IJNVO

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In recent years, more and more workflow applications have been developed to execute on various kinds of cloud platforms. Although many cloud-based workflow management and enactment systems have been proposed, there are still many challenges when deploying and executing workflows on various kinds of real-world cloud platform. In this paper, we present a lightweight framework, namely cloud-oriented workflow optimisation middleware (CWOM), which is designed for easing the work of optimising the workflow execution efficiency as well as the work of realising fine-grained workflow management. The proposed CWOM is implemented as a plug-in middleware that can interact with the other workflow services and therefore provide more desirable services for workflow applications. Another advantage of our CWOM is that its services are loosely coupled with other cloud services, which makes it more flexible and configurable in most of the real-world cloud platforms. To investigate the effectiveness of the proposed system, we deploy the prototype implementation of CWOM in a campus-based cloud platform, and the experimental results indicate that it can significantly improve the delivered QoS and enhance the service level offered by conventional workflow solutions.

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