مشخصات مقاله:
عنوان فارسی مقاله:
عنوان انگلیسی مقاله:
کلمات کلیدی مقاله:
مناسب برای رشته های دانشگاهی زیر:
مهندسی کامپیوتر
مناسب برای گرایش های دانشگاهی زیر:
مهندسی نرم افزار، رایانش ابری
وضعیت مقاله انگلیسی و ترجمه:
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فهرست مطالب:
چکیده
1. معرفی
2. کارهای مرتبط
3. محیط ابر تحمل پذیر اشکال
3.1 بررسی اجمالی سیستم
2.3 مصرف توان نود
3.3 توضیحات بارکاری و خرابی
4.3 توصیف نمونه
5.3 الگوریتم های زمان بندی
4. ارزیابی و نتایج
1.4 معیارهای ارزیابی
5 نتیجه گیری
منابع
قسمتی از مقاله انگلیسی و ترجمه آن:
Abstract
As data centres continue to grow in size and complexity in order to respond to the increasing demand for computing resources, failures become the norm instead of an exception. To provide dependability at scale, traditional techniques to tolerate faults focus on reactive, redundant schemes. While the former relies on the checkpointing/restart of a job (which could incur significant overhead in a large-scale system), the latter replicates tasks, thus consuming extra resources to achieve higher reliability and availability of computing environments. Proactive fault-tolerance in large systems represents a new trend to avoid, cope with and recover from failures. However, different fault-tolerance schemes provide different levels of computing environment dependability at diverse costs to both providers and consumers.
چکیده
As data centres continue to grow in size and complexity in order to respond to the increasing demand for computing resources, failures become the norm instead of an exception. To provide dependability at scale, traditional techniques to tolerate faults focus on reactive, redundant schemes. While the former relies on the checkpointing/restart of a job (which could incur significant overhead in a large-scale system), the latter replicates tasks, thus consuming extra resources to achieve higher reliability and availability of computing environments. Proactive fault-tolerance in large systems represents a new trend to avoid, cope with and recover from failures. However, different fault-tolerance schemes provide different levels of computing environment dependability at diverse costs to both providers and consumers.