مقاله انگلیسی رایگان در مورد توزیع موثر درخواست ها در محیط محاسبات ابری – الزویر ۲۰۱۹

elsevier

 

مشخصات مقاله
ترجمه عنوان مقاله توزیع موثر درخواست ها در محیط محاسبات ابری متعهد با استفاده از توزیع آماری
عنوان انگلیسی مقاله Efficient distribution of requests in federated cloud computing environments utilizing statistical multiplexing
انتشار مقاله سال ۲۰۱۹
تعداد صفحات مقاله انگلیسی ۳۳ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله پژوهشی (Research article)
مقاله بیس این مقاله بیس نمیباشد
نمایه (index) scopus – master journals – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
۴٫۶۳۹ در سال ۲۰۱۷
شاخص H_index ۸۵ در سال ۲۰۱۸
شاخص SJR ۰٫۸۴۴ در سال ۲۰۱۸
رشته های مرتبط مهندسی کامپیوتر
گرایش های مرتبط رایانش ابری
نوع ارائه مقاله
ژورنال
مجله / کنفرانس نسل آینده سیستم های کامپیوتری – Future Generation Computer Systems
دانشگاه Department of Computer Engineering – Sharif University of Technology – Iran
کلمات کلیدی محاسبات ابری، فدراسیون ابر، چند ابر، تقسیم درخواست، توزیع آماری
کلمات کلیدی انگلیسی Cloud Computing, Cloud Federation, Multiclouds, Request Partitioning, Statistical Multiplexing
شناسه دیجیتال – doi
https://doi.org/10.1016/j.future.2018.08.032
کد محصول E10263
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فهرست مطالب مقاله:
Highlights
Abstract
Keywords
۱ Introduction
۲ Real world example
۳ Related work
۴ The framework & theoretical results
۵ Simulation
۶ The question of fairness
۷ Conclusion & future works
References
Vitae

بخشی از متن مقاله:
Abstract

One of the main questions in cloud computing environments is how to efficiently distribute user requests or Virtual Machines (VMs) based on their resource needs over time. This question is also an important one when dealing with a cloud federation environment where rational cloud service providers are collaborating together by sharing customer requests. By considering intrinsic aspects of the cloud computing model one can propose request distribution methods that play on the strengths of this computing paradigm. In this paper we look at statistical multiplexing and server consolidation as such a strength and examine the use of the coefficient of variation and other related statistical metrics as objective functions which can be used in deciding on the request distribution mechanism. The complexity of using these objective functions is analyzed and heuristic methods which enable efficient request partitioning in a feasible time are presented & compared.

Introduction

Federated cloud computing environments have recently emerged as a trending topic in cloud computing. Here Cloud Service Providers (CSPs) collaborate by delegating some (or all) of their customers’ requests to other CSPs. This 5 is done due to various reasons, be it overloaded servers in the federating CSP (i.e. the CSP that delegates parts of its request load to the federated CSP), the need to adhere to customer Service Level Agreements (SLAs) in special circumstances where the cloud provider cannot guarantee quality attributes, etc. Out of the decisions that must be taken in order to operate in such a federated envi10 ronment, one of the most crucial is which requests to federate and how should this federation take place keeping in mind the CSPs currently participating in the federation. The answer to this question must be one which is efficient and fair for all participating CSPs and incentivizes them to partake in the federation mechanism. How we model and evaluate this based on various objective 15 functions is an important consideration in this area. In this paper we emphasize a request distribution mechanism that focuses on multitenancy as a key factor that enables the cloud computing paradigm, providing many of the benefits of this paradigm from a cloud service provider perspective. The federation structure used here can be seen in Figure 1. Cus20 tomer requests are given to a Federation Broker who distributes them between CSPs which are cooperating in a cloud federation. Such a broker must consider multiple criteria when distribution occurs, including those relating to performance, pricing, quality of service, etc. The criteria (and its related objective functions) which we examine is to ensure request partitioning is efficient with 25 regards to utilizing multitenancy. To this end, different objective functions will be considered, including those that impact statistical multiplexing, as we will show throughout the rest of this section.

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