مقاله انگلیسی رایگان در مورد ارزیابی کیفیت خدمات اطلاعاتی محیط محاسبات ابری – IEEE 2017

 

مشخصات مقاله
ترجمه عنوان مقاله ارزیابی کیفیت خدمات اطلاعاتی محیط محاسبات ابری بر اساس کلان داده
عنوان انگلیسی مقاله Information service quality evaluation study of cloud computing environment based on big data
انتشار مقاله سال 2017
تعداد صفحات مقاله انگلیسی 5 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه IEEE
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مهندسی کامپیوتر
گرایش های مرتبط رایانش ابری
مجله کنفرانس بین المللی محاسبات ابر و تحلیل کلان داده – International Conference on Cloud Computing and Big Data Analysis
دانشگاه National Defense Information Academy – Wuhan – China
کلمات کلیدی کلان داده؛ محیط محاسبات ابری؛ سرویس اطلاعاتی؛ ارزیابی کیفیت
کلمات کلیدی انگلیسی big data; cloud computing enfironment; information service; quality evaluation
شناسه دیجیتال – doi
https://doi.org/10.1109/ICCCBDA.2017.7951917
کد محصول E9184
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بخشی از متن مقاله:
I. INTRODUCTION

Internet + era, cloud computing environment is the basic information service environment, big data is a basic support, information environment play the service efficiency of the cloud computing environment based on large data elements numerous, complicated structure, close-knit and cloud computing environment of information service quality directly affect the big data application advantages into full play, to appraise the future scale of Internet + information environment. Cloud computing environment, therefore, to improve information service quality evaluation research based on large data cloud computing environment construction efficiency is of great significance [1]. II. CLOUD COMPUTING ENVIRONMENT INFORMATION SERVICE QUALITY EVALUATION PROCESS Cloud computing environment based on large data information service quality can adopt the method of fuzzy comprehensive evaluation are analyzed [2]. The characteristics of large data of Internet + cloud computing environment, contains many elements, these elements jointly constructed for cloud computing environment based on large data. According to the building in front of the cloud computing environment information service quality evaluation index system, a two-level fuzzy comprehensive evaluation method can be used to build a cloud computing environment information service quality evaluation model, basic steps, as shown in Figure 1, including establishing evaluation index system of evaluation index set semantics, determine the evaluation set, determine the weight assembly of evaluation index, establishing the comprehensive fuzzy Cloud computing environment information service quality evaluation involves numerous elements, to consider the factors is more complex, because of the lack of cloud computing environment based on large data information service quality evaluation experience, therefore in constructing effectiveness evaluation index system, need to attach great importance to the collection of raw data, give full play to people’s subjective initiative. Cloud computing application environment, which can be found that the core of the cloud computing environment based on large data elements including data transfer, data processing, information service, information security and information management of five elements. As a result, the data transfer capacity (U I), data processing capacity (U 2), information service (U3), information security ability (U4) and data management capabilities (Us) five level indicators based on big data to describe the construction efficiency of cloud computing environment is feasible. According to this method can generate secondary indicators of level indicator, etc, are no longer here. Cloud computing environment information service quality evaluation index system, index dimensional units at various levels is not the same, in their evaluations are difficult to compare in the same category, which requires the index data are dimensionless processing [3]. Based on large data cloud computing environment information service elements is numerous, the relationship between the complex, difficult to accurate analysis of indicators. Therefore, in the relevant data of index system dimensionless processing, index has the characteristics of typical interval is changed.

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