مقاله انگلیسی رایگان در مورد طرح خوشه بندی توان موثر برای محيط محاسبات لبه موبایل 5G – اسپرینگر 2018

 

مشخصات مقاله
ترجمه عنوان مقاله طرح خوشه بندی توان موثر برای محيط محاسبات لبه موبایل 5G
عنوان انگلیسی مقاله Power Efficient Clustering Scheme for 5G Mobile Edge Computing Environment
انتشار مقاله سال 2018
تعداد صفحات مقاله انگلیسی 10 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه اسپرینگر
مقاله بیس این مقاله بیس نمیباشد
نمایه (index) Scopus – Master Journal List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
2.850 در سال 2018
شاخص H_index 79 در سال 2019
شاخص SJR 0.426 در سال 2018
شناسه ISSN 1572-8153
شاخص Quartile (چارک) Q2 در سال 2018
رشته های مرتبط مهندسی کامپیوتر
گرایش های مرتبط رایانش ابری، مهندسی الگوریتم ها و محاسبات، مهندسی نرم افزار، معماری سیستم های کامپیوتری
نوع ارائه مقاله
ژورنال
مجله / کنفرانس شبکه های موبایل و برنامه های کاربردی – Mobile Networks and Applications
دانشگاه  School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, South Korea
کلمات کلیدی توابع شبکه مجازی (VNFs)، محاسبات لبه موبایل، خوشه بندی توان کارامد
کلمات کلیدی انگلیسی Virtual Network Functions (VNFs)، Mobile Edge Computing (MEC)، Power-efficient clustering
شناسه دیجیتال – doi
https://doi.org/10.1007/s11036-018-1164-2
کد محصول E11266
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
دانلود رایگان مقاله دانلود رایگان مقاله انگلیسی
سفارش ترجمه این مقاله سفارش ترجمه این مقاله

 

فهرست مطالب مقاله:
Abstract

1- Introduction

2- System model

3- Proposed power consumption model

4- Proposed Power Efficient Clustering Scheme (PECS)

5- Numerical results

6- Conclusion

References

 

بخشی از متن مقاله:

Abstract

Mobile edge computing (MEC), which is an evolution of cloud computing, is acknowledged as a promising technology for meeting low latency and bandwidth efficiency required in fifth generation (5G) era. Accordingly, the enlargement of distributed MEC installments will be realized and their power consumption might be a significant problem in terms of operating costs for service providers. Thus, this paper proposes a theoretical framework for MEC server clustering to minimize power consumption of the MEC environment. To do this, considering power consumption behavior of MEC servers using CPUs with dynamic voltage frequency scaling, we propose a power-efficient clustering scheme (PECS) that minimizes power consumption of MEC servers by obtaining the optimal number of clusters through convex optimization. Numerical results reveal the proposed PECS reduces power consumption of the MEC environment by 12.32% relative to an existing scheme while sustaining average delay of inflows processed in MEC servers at the acceptable level without turning off MEC servers.

Introduction

Mobile edge computing (MEC), which sustains multiple distributed edge servers by moving computing points from centralized points to near end-user points, has emerged as a promising technology for pervasive fifth generation (5G) services such as internet of things (IoT), device-to-device (D2D), and low-latency video streaming (e.g., virtual reality/ augmented reality video streaming) etc., to meet low latency and bandwidth efficiency [1–4]. Subsequently, the enlargement of distributed MEC installments will be realized and their power consumption might be a significant issue in terms of operating costs for service providers. Thus, with much attention being directed towards energy efficient data center management, power consumption is also expected to be an important criterion in MEC management along with delay. According to iGR [5], the number of U.S. MEC installations is expected to reach 563,000 divided into 2,000 locations by 2026. They generate more than 2.66 TWh annually in the U.S. alone and the corresponding cost amounts to more than 217 million dollars when the average power consumption of each MEC installation is 300W and the power utilization effectiveness (PUE) is 1.8 [6]. Moreover, the PUE of MEC is getting worse since MEC is restricted to being located physically near the end-user point, whereas a traditional data center can reduce power consumption by more than 20% by locating the data center in a cool climate region with free cooling [7]. To date, researches on MEC has mostly focused on reducing delay [8, 9]. MEC is implemented as a virtualized platform instead of a custom hardware appliance, leveraging recent advances in network function virtualization (NFV) [1, 10, 11].

دیدگاهتان را بنویسید

نشانی ایمیل شما منتشر نخواهد شد. بخش‌های موردنیاز علامت‌گذاری شده‌اند *

دکمه بازگشت به بالا