|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|93181||2018||28 صفحه PDF||سفارش دهید||10045 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Future Generation Computer Systems, Volume 79, Part 2, February 2018, Pages 630-642
The development of an efficient Early Warning System (EWS) is essential for the prediction and prevention of imminent natural hazards. In addition to providing a computationally intensive infrastructure with extensive data transfer, high-execution reliability and hard-deadline satisfaction are important requirements of EWS scenario processing. This is due to the fact that EWS has a limited window of opportunity to discern if a scene shows signs of an impending natural disaster. In this paper, the scheduling component of the EWS scenario is investigated and an efficient hybrid algorithm for the urgent workflows scheduling is proposed. The developed algorithm is based on traditional heuristic and meta-heuristic approaches along with state-of-the-art cloud computing principles.