ارائه یک روش کارا برای تخصیص منابع در رایانش مه با در نظر گرفتن شرایط ازدحام درخواست ها
محورهای موضوعی : مهندسی برق و کامپیوترسمیرا انصاری مقدم 1 , سميرا نوفرستي 2 , مهري رجايي 3
1 - دانشگاه سیستان و بلوچستان
2 - دانشگاه سيستان و بلوچستان
3 - دانشگاه سیستان و بلوچستان
کلید واژه: ازدحام درخواست‌ها, تخصیص منابع, رایانش مه, زمان‌بندی, قرارگیری درخواست,
چکیده مقاله :
مراکز داده ابر به دلیل فاصله زیاد از کاربران نهایی اغلب در مواجه‌شدن با میلیون‌ها درخواست ذخیره‌سازی و پردازشی حساس به تأخیر، ناموفق عمل می‌کنند. درخواست‌های حساس به تأخیر نیاز دارند که پاسخ خود را حتی در شرایط ازدحام درخواست‌ها در شبکه، قبل از به اتمام رسیدن مهلت زمانی از پیش تعیین شده دریافت کنند. برای رفع این نیاز، معماری رایانش مه معرفی شد که سرویس‌های محاسباتی، ذخیره‌سازی و ارتباطی را در لبه شبکه برای کاربران فراهم می‌کند. از جمله چالش‌های رایانش مه چگونگی تخصیص منابع گره‌های مه و ابر به درخواست‌های کاربران در شرایط ازدحام، برای رسیدن به بیشترین نرخ پذیرش و کمترین زمان پاسخ درخواست‌ها است. گره‌های مه قدرت پردازشی و ذخیره‌سازی محدودی دارند و در نتیجه در شرایط ازدحام درخواست‌ها، کارایی مناسبی ندارند. در این مقاله روشی کارا برای تخصیص منابع در رایانش مه پیشنهاد می‌شود که به منظور مقابله با چالش مذکور، با توجه به وضعیت منابع آزاد گره و شرایط ازدحام، در مورد محل قرارگیری و اجرای درخواست (گره مه یا ابر) تصمیم‌گیری می‌کند. بر اساس آزمایش‌های صورت‌گرفته، روش پیشنهادی بر اساس معیارهای متوسط زمان پاسخ و درصد درخواست‌های لغوشده عملکرد بهتری در مقایسه با سایر روش‌ها دارد.
Cloud data centers often fail to cope with the millions of delay-sensitive storage and computational requests due to their long distance from end users. A delay-sensitive request requires a response before its predefined deadline expires, even when the network has a high load of requests. Fog computing architecture, which provides computation, storage and communication services at the edge of the network, has been proposed to solve these problems. One of the fog computing challenges is how to allocate cloud and fog nodes resources to user requests in congestion conditions to achieve a higher acceptance rate of user requests and minimize their response time. Fog nodes have limited storage and computational power, and hence their performance is significantly reduced due to high load of user requests. This paper proposes an efficient resource allocation method in fog computing that decides where (fog or cloud) to process the requests considering the available resources of fog nodes and congestion conditions. According to the experimental results, the performance of the proposed method is better compared with existing methods in terms of average response time and percentage of failed requests.
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