دانلود مقاله ISI انگلیسی شماره 74192
عنوان فارسی مقاله

دستیابی به MapReduce پاسخگو در رایانش ابری

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
74192 2014 13 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
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عنوان انگلیسی
Achieving Accountable MapReduce in cloud computing
منبع

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

Journal : Future Generation Computer Systems, Volume 30, January 2014, Pages 1–13

کلمات کلیدی
پاسخگو؛ MapReduce؛ رایانش ابری
پیش نمایش مقاله
پیش نمایش مقاله دستیابی به MapReduce پاسخگو در رایانش ابری

چکیده انگلیسی

MapReduce is a programming model that is capable of processing large data sets in distributed computing environments. The original MapReduce model was designed to be fault-tolerant in case of various network abnormalities. However, fault-tolerance does not guarantee that each working machine will be completely accountable; when nodes are malicious, they may intentionally misrepresent the processing result during mapping or reducing, and they may thus make the final results inaccurate and untrustworthy. In this paper, we propose Accountable MapReduce, which forces each machine to be held responsible for its behaviors. In our approach, we set up a group of auditors to perform an Accountability Test (AA-test) that checks all of the working machines and detects malicious nodes in real time. The AA-test can be implemented with different options depending upon how the auditors are assigned. To optimize the utilization resource, we also formalize the Optimal Worker and Auditor Assignment (OWAA) problem, which is aimed at finding the optimal number of workers and auditors in order to minimize the total processing time. Our evaluation results show that the AA-test can be practically and effectively applied to existing cloud platforms employing MapReduce.

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