دانلود مقاله ISI انگلیسی شماره 95311
ترجمه فارسی عنوان مقاله

الگوریتم پیشرفته هوشمند قطره آب برای برنامه ریزی گردش کار در محیط محاسبات ابری

عنوان انگلیسی
An extended Intelligent Water Drops algorithm for workflow scheduling in cloud computing environment
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
95311 2018 23 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Egyptian Informatics Journal, Volume 19, Issue 1, March 2018, Pages 33-55

ترجمه کلمات کلیدی
پردازش ابری، الگوریتم های برنامه ریزی، مدیریت منابع، قطره آب هوشمند برنامه ریزی گردش کار، الگوریتم های مبتنی بر طبیعی،
کلمات کلیدی انگلیسی
Cloud computing; Scheduling algorithms; Resource management; Intelligent Water Drops; Workflow scheduling; Natural-based algorithms;
پیش نمایش مقاله
پیش نمایش مقاله  الگوریتم پیشرفته هوشمند قطره آب برای برنامه ریزی گردش کار در محیط محاسبات ابری

چکیده انگلیسی

Cloud computing is emerging as a high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. Many resource management methods may enhance the efficiency of the whole cloud computing system. The key part of cloud computing resource management is resource scheduling. Optimized scheduling of tasks on the cloud virtual machines is an NP-hard problem and many algorithms have been presented to solve it. The variations among these schedulers are due to the fact that the scheduling strategies of the schedulers are adapted to the changing environment and the types of tasks. The focus of this paper is on workflows scheduling in cloud computing, which is gaining a lot of attention recently because workflows have emerged as a paradigm to represent complex computing problems. We proposed a novel algorithm extending the natural-based Intelligent Water Drops (IWD) algorithm that optimizes the scheduling of workflows on the cloud. The proposed algorithm is implemented and embedded within the workflows simulation toolkit and tested in different simulated cloud environments with different cost models. Our algorithm showed noticeable enhancements over the classical workflow scheduling algorithms. We made a comparison between the proposed IWD-based algorithm with other well-known scheduling algorithms, including MIN-MIN, MAX-MIN, Round Robin, FCFS, and MCT, PSO and C-PSO, where the proposed algorithm presented noticeable enhancements in the performance and cost in most situations.