دوره 15، شماره 2 - ( مجله کنترل، جلد 15، شماره 2، تابستان 1400 )                   جلد 15 شماره 2,1400 صفحات 96-81 | برگشت به فهرست نسخه ها

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Sadeghi Hesar A, Kamel Tabakh S R, Houshmand M. Task Scheduling Using the PSO-IWD Hybrid Algorithm in Cloud Computing with Heterogeneous Resources. JoC. 2021; 15 (2) :81-96
URL: http://joc.kntu.ac.ir/article-1-627-fa.html
صادقی حصار علیرضا، کامل طباخ سید رضا، هوشمند محبوبه. زمان‌بندی وظایف با استفاده از الگوریتم ترکیبی PSO-IWD در محیط‌های محاسبات ابری با منابع ناهمگن. مجله کنترل. 1400; 15 (2) :96-81

URL: http://joc.kntu.ac.ir/article-1-627-fa.html


1- گروه مهندسی کامپیوتر، واحد مشهد، دانشگاه آزاد اسلامی، مشهد، ایران
چکیده:   (8448 مشاهده)
زمان‌بندی بهینه وظایف یکی از مهمترین چالش‌ها برای دست‌یابی به عملکرد مطلوب در محیط‌های توزیع‌شده مانند محاسبات ابری است. هدف از زمان‌بندی وظایف، تخصیص وظایف به منابع پردازشی است بگونه‌ای که برخی از معیارهای عملکردِ سیستم مانند زمان اجرا یا توازی بهینه شوند. زمان‌بندی وظایف یک مسئله NP-کامل است، از این رو از الگوریتم‌های اکتشافی یا فرااکتشافی برای حل آن استفاده می‌شود. چون ارائه‌دهندگان ابر، منابع محاسباتی را بر مبنای مدل «پرداخت به میزان استفاده» ارائه می‌کنند، الگوریتم زمان‌بندی وظایف بشدت هزینه کاربران در ابر را تحت تاثیر قرار می‌دهد. در این مقاله یک الگوریتم زمان‌بندی وظایف جدید بر اساس بهینه‌سازی ازدحام ذرات بعنوان یک روش فرااکتشافی پیشنهاد می‌شود که وظایف کاربران را به منابع آزاد در محیط‌های محاسبات ابری تخصیص می‌دهد. برای تقویت عملکرد روش بهینه‌سازی ازدحام ذرات از نظر سرعت همگرایی الگوریتم قطره‌های آب هوشمند اِعمال می‌شود. نتایج اجرای این الگوریتم روی گراف‌های تصادفی، بهبود قابل توجه کاراییِ روش پیشنهادی در مقایسه با سایر الگوریتم‌های زمان‌بندی وظایف را نشان دادند.    
متن کامل [PDF 905 kb]   (29 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: تخصصي
دریافت: 1397/8/6 | پذیرش: 1399/4/7 | انتشار الکترونیک پیش از انتشار نهایی: 1399/4/20 | انتشار: 1400/4/13

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