دانلود مقاله انگلیسی رایگان:زمانبندی چند هدفه گردش کار علمی علمی شدید در مه - 2020
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  • Multi-objective scheduling of extreme data scientific workflows in Fog Multi-objective scheduling of extreme data scientific workflows in Fog
    Multi-objective scheduling of extreme data scientific workflows in Fog

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    Multi-objective scheduling of extreme data scientific workflows in Fog


    ترجمه فارسی عنوان مقاله:

    زمانبندی چند هدفه گردش کار علمی علمی شدید در مه


    منبع:

    Sciencedirect - Elsevier - Future Generation Computer Systems, 106 (2020) 171-184: doi:10:1016/j:future:2019:12:054


    نویسنده:

    Vincenzo De Maio a, Dragi Kimovski


    چکیده انگلیسی:

    The concept of ‘‘extreme data’’ is a recent re-incarnation of the ‘‘big data’’ problem, which is distinguished by the massive amounts of information that must be analyzed with strict time requirements. In the past decade, the Cloud data centers have been envisioned as the essential computing architectures for enabling extreme data workflows. However, the Cloud data centers are often geographically distributed. Such geographical distribution increases offloading latency, making it unsuitable for processing of workflows with strict latency requirements, as the data transfer times could be very high. Fog computing emerged as a promising solution to this issue, as it allows partial workflow processing in lower-network layers. Performing data processing on the Fog significantly reduces data transfer latency, allowing to meet the workflows’ strict latency requirements. However, the Fog layer is highly heterogeneous and loosely connected, which affects reliability and response time of task offloading. In this work, we investigate the potential of Fog for scheduling of extreme data workflows with strict response time requirements. Moreover, we propose a novel Pareto-based approach for task offloading in Fog, called Multi-objective Workflow Offloading (MOWO). MOWO considers three optimization objectives, namely response time, reliability, and financial cost. We evaluate MOWO workflow scheduler on a set of real-world biomedical, meteorological and astronomy workflows representing examples of extreme data application with strict latency requirements.
    Keywords: Scheduling | Scientific workflows | Fog computing | Task offloading | Monte-Carlo simulation | Multi-objective optimization


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 14
    حجم فایل: 993 کیلوبایت

    قیمت: رایگان


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