مقاله انگلیسی رایگان در مورد محاسبات ابری سیار برای تخلیه محاسباتی – الزویر ۲۰۱۸

مقاله انگلیسی رایگان در مورد محاسبات ابری سیار برای تخلیه محاسباتی – الزویر ۲۰۱۸

 

مشخصات مقاله
ترجمه عنوان مقاله محاسبات ابری سیار برای تخلیه محاسباتی: مسائل و چالش ها
عنوان انگلیسی مقاله Mobile cloud computing for computation offloading: Issues and challenges
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی ۱۶ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله مروری (review article)
مقاله بیس این مقاله بیس نمیباشد
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مهندسی کامپیوتر
گرایش های مرتبط رایانش ابری، الگوریتم ها و محاسبات
نوع ارائه مقاله
ژورنال
مجله / کنفرانس محاسبات کاربردی و انفورماتیک – Applied Computing and Informatics
دانشگاه  Technical University of Munich – TUM – Munich – Germany
کلمات کلیدی پردازش ابری؛ محاسبات ابری موبایل؛ تخلیه محاسباتی؛ الگوریتم ها؛ جزء بندی
کلمات کلیدی انگلیسی Cloud computing; Mobile cloud computing; Computational offloading; Algorithms; Partitioning
شناسه دیجیتال – doi
http://dx.doi.org/10.1016/j.aci.2016.11.002
کد محصول E9968
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
Keywords
۱ Introduction
۲ Concepts and background
۳ Offloading approaches
۴ Comparison of offloading frameworks in mobile cloud computing
۵ General issues and challenges in computation offloading for MCC
۶ Conclusion
Acknowledgments
References

بخشی از متن مقاله:
Abstract

Despite the evolution and enhancements that mobile devices have experienced, they are still considered as limited computing devices. Today, users become more demanding and expect to execute computational intensive applications on their smartphone devices. Therefore, Mobile Cloud Computing (MCC) integrates mobile computing and Cloud Computing (CC) in order to extend capabilities of mobile devices using offloading techniques. Computation offloading tackles limitations of Smart Mobile Devices (SMDs) such as limited battery lifetime, limited processing capabilities, and limited storage capacity by offloading the execution and workload to other rich systems with better performance and resources. This paper presents the current offloading frameworks, computation offloading techniques, and analyzes them along with their main critical issues. In addition, it explores different important parameters based on which the frameworks are implemented such as offloading method and level of partitioning. Finally, it summarizes the issues in offloading frameworks in the MCC domain that requires further research.

Introduction

The main goal of CC is to allow IT departments to focus on 55 their businesses and projects instead of just taking care of their 56 data centers and keeping them working [2,18,20]. CC is a new 57 concept that aims to provide computational resources as ser58 vices in a quick manner, on demand, and paying as per usage. 59 The CC paradigm is presented in three cloud delivery models: 60 Infrastructure-as-a-Service (IaaS), Platform-as-a-Service 61 (PaaS), and Software-as-a-Service (SaaS) as shown in Fig. 1. 62 According to Gartner [3], CC will have in 2016 a Global Com63 pounded Annual Growth Rate (CAGR) of IaaS: 41%, PaaS: 64 26.6% and SaaS: 17.4%. 65 Recently, user preferences for computing have changed 66 because of the latest developments and enhancements in 67 mobile computing technologies. Several reports and studies 68 have presented the importance of MCC and its impact on 69 mobile clients and enterprises. For instance, and according 70 to a recent study by ABI Research, more than 240 million busi71 ness will use cloud services through mobile devices by 2015 and 72 this will push the revenue of the MCC to $5.2 billion [11]. 73 Moreover, the usage of smartphones has increased rapidly in 74 various domains, including enterprise, management of infor75 mation systems, gaming, e-learning, entertainment, gaming, 76 and health care. Although the predictions that mobile devices 77 will be dominating the future computing devices, mobile 78 devices along with their applications are still restricted by some 79 limitations such as the battery life, processor potential, and the 80 memory capacity of the SMDs [31].

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