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  • Open Access

    ARTICLE

    Failure Prediction for Scientific Workflows Using Nature-Inspired Machine Learning Approach

    S. Sridevi*, Jeevaa Katiravan

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 223-233, 2023, DOI:10.32604/iasc.2023.031928

    Abstract Scientific workflows have gained the emerging attention in sophisticated large-scale scientific problem-solving environments. The pay-per-use model of cloud, its scalability and dynamic deployment enables it suited for executing scientific workflow applications. Since the cloud is not a utopian environment, failures are inevitable that may result in experiencing fluctuations in the delivered performance. Though a single task failure occurs in workflow based applications, due to its task dependency nature, the reliability of the overall system will be affected drastically. Hence rather than reactive fault-tolerant approaches, proactive measures are vital in scientific workflows. This work puts forth an attempt to concentrate on… More >

  • Open Access

    ARTICLE

    Efficient Computation Offloading of IoT-Based Workflows Using Discrete Teaching Learning-Based Optimization

    Mohamed K. Hussein1,*, Mohamed H. Mousa1,2

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3685-3703, 2022, DOI:10.32604/cmc.2022.026370

    Abstract As the Internet of Things (IoT) and mobile devices have rapidly proliferated, their computationally intensive applications have developed into complex, concurrent IoT-based workflows involving multiple interdependent tasks. By exploiting its low latency and high bandwidth, mobile edge computing (MEC) has emerged to achieve the high-performance computation offloading of these applications to satisfy the quality-of-service requirements of workflows and devices. In this study, we propose an offloading strategy for IoT-based workflows in a high-performance MEC environment. The proposed task-based offloading strategy consists of an optimization problem that includes task dependency, communication costs, workflow constraints, device energy consumption, and the heterogeneous characteristics… More >

  • Open Access

    ARTICLE

    Rapid Profiling and Characterization of the Multicomponents from the Root and Rhizome of Salvia miltiorrhiza by Ultra-High Performance Liquid Chromatography/Ion Mobility-Quadrupole Time-of-Flight Mass Spectrometry in Combination with Computational Peak Annotation Workflows

    Boxue Chen1,#, Hongda Wang1,#, Meiyu Liu1, Wandi Hu1, Yuexin Qian1, Jiali Wang1, Jie Liu1, Xue Li1, Jing Wang2, Wenzhi Yang1,*

    Phyton-International Journal of Experimental Botany, Vol.91, No.5, pp. 1073-1088, 2022, DOI:10.32604/phyton.2022.019399

    Abstract Herbal components characterization represents a challenging task because of the co-existing of multiple classes of naturally occurring compounds with wide spans of polarity, molecular mass, and the ubiquitous isomerism. The root and rhizome of Salvia miltiorrhiza have been utilized as a reputable traditional Chinese medicine Salviae Miltiorrhizae Radix et Rhizoma (Dan-Shen) in the treatment of cardiovascular disease. Herein, a dimension-enhanced ultra-high performance liquid chromatography/ion mobility/quadrupole time-of-flight mass spectrometry approach in combination with intelligent peak annotation workflows was established aimed to rapidly characterize the multicomponents from S. miltiorrhiza. Due to the sufficient optimization, satisfactory chromatography separation was enabled on an HSS… More >

  • Open Access

    ARTICLE

    Formal Approach to Workflow Application Fragmentations Over Cloud Deployment Models

    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 >

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