Ehab Nabiel Al-Khanak^1,*, Sai Peck Lee², Saif Ur Rehman Khan³, Navid Behboodian⁴, Osamah Ibrahim Khalaf⁵, Alexander Verbraeck⁶, Hans van Lint¹

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3265-3282, 2021, DOI:10.32604/cmc.2021.015409

Abstract Scientific Workflow Applications (SWFAs) can deliver collaborative tools useful to researchers in executing large and complex scientific processes. Particularly, Scientific Workflow Scheduling (SWFS) accelerates the computational procedures between the available computational resources and the dependent workflow jobs based on the researchers’ requirements. However, cost optimization is one of the SWFS challenges in handling massive and complicated tasks and requires determining an approximate (near-optimal) solution within polynomial computational time. Motivated by this, current work proposes a novel SWFS cost optimization model effective in solving this challenge. The proposed model contains three main stages: (i) scientific workflow application, (ii) targeted computational environment,… More >

Hyun Ahn, Kwanghoon Pio Kim^*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3071-3088, 2021, DOI:10.32604/cmc.2021.015280

Abstract Workflow management technologies have been dramatically improving their deployment architectures and systems along with the evolution and proliferation of cloud distributed computing environments. Especially, such cloud computing environments ought to be providing a suitable distributed computing paradigm to deploy very large-scale workflow processes and applications with scalable on-demand services. In this paper, we focus on the distribution paradigm and its deployment formalism for such very large-scale workflow applications being deployed and enacted across the multiple and heterogeneous cloud computing environments. We propose a formal approach to vertically as well as horizontally fragment very large-scale workflow processes and their applications and… More >

Kaita Ito*, Satoshi Minamoto, Takuya Kadohira, Makoto Watanabe, Masahiko Demura

The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 134-134, 2019, DOI:10.32604/icces.2019.05440

Abstract In the Materials Integration (MI) system, workflow designers and players are implemented as ones of the core subsystems. When the user wants to predict a certain material parameter by using the MI system, the user selects a prediction module in the workflow designer that can output the objective parameter. If the all required input parameters of the prediction module are not given directly, further modules can be connected.
Each input and output parameters of the prediction module on the MI system is directly associated with one term of material science and engineering. It is not defined as a specific… More >