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بهینه‌سازی چند هدفه‌ی مسئله‌ی زمان‌بندی کار در پردازش ابری

نویسندگان

دانشکده ریاضی و کامپیوتر، دانشگاه شهید باهنر، کرمان، ایران

چکیده

در محیط ابر، زمان‌بندی بهینه کارها، به عوامل زیادی همچون زمان اتمام کارها، تاخیر و تعادل بار روی ماشین‌ها بستگی دارد. اما توجه اصلی سایر مقالات انجام شده فقط به کمینه کردن زمان اتمام کارهاست. در این مقاله، پارامترهای موثر بر کیفیت خدمات یعنی کمینه‌ی زمان اتمام کارها، کمینه‌ی میزان دیرکرد از موعد تحویل و بیشینه‌ی تعادل بار روی ماشین‌ها به عنوان توابع هدف، همزمان در نظر گرفته شده است. زمان‌بندی جزء مسائل پیچیده‌ای است که برای آن، راه‌حل از مرتبه‌ی چندجمله‌ای وجود ندارد و به همین دلیل از الگوریتم‌های فرا اکتشافی مانند بهینه‌سازی گروه ذرات، شبیه‌سازی حرارت، جستجوی ممنوعه و الگوریتم ژنتیک چندهدفه استفاده شده است. نتایج شبیه‌سازی نشان داده است که بین الگوریتم‌های تک‌هدفه، الگوریتم بهینه‌سازی گروه ذرات در زمان کمتری اجرا شده و حتی برای تعداد 30 کار، از نظر بهینه‌سازی تابع هدف، قابل رقابت با الگوریتم‌های چندهدفه می‌باشد. در تعداد کار زیاد، الگوریتم‌های
چندهدفه، از نظر مدت زمان اجرا و همچنین بهینه‌سازی توابع هدف، مناسب‌ترند. زیرا الگوریتم ژنتیک مرتب‌شده یا رتبه‌بندی‌شده‌ی نامغلوب، توابع هدف را به صورت مجزا در نظر گرفته و بنابراین امکان انتخاب جواب‎‎‌های مطلوب را میان جواب‌های غیر برتر در راستای مصالحه بین اهدف مختلف را دارد.

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علوم رایانش و فناوری اطلاعات
دوره 18، شماره 2
پاییز و زمستان
آذر 1399