طرح خوشه بندی توان موثر برای محيط محاسبات لبه موبایل 5G
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طرح خوشه بندی توان موثر برای محيط محاسبات لبه موبایل 5G

عنوان فارسی 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
مجله/کنفرانس: شبکه های موبایل و برنامه های کاربردی - Mobile Networks and Applications
رشته های تحصیلی مرتبط: مهندسی کامپیوتر
گرایش های تحصیلی مرتبط: رایانش ابری، مهندسی الگوریتم ها و محاسبات، مهندسی نرم افزار، معماری سیستم های کامپیوتری
کلمات کلیدی فارسی: 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
نمایه: Scopus - Master Journal List - JCR
شناسه دیجیتال (DOI): https://doi.org/10.1007/s11036-018-1164-2
دانشگاه: School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, South Korea
ناشر: اسپرینگر - Springer
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2018
ایمپکت فاکتور: 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
فرمت مقاله انگلیسی: pdf
تعداد صفحات مقاله انگلیسی: 10
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
کد محصول: E11266
فهرست انگلیسی مطالب

Abstract


1- Introduction


2- System model


3- Proposed power consumption model


4- Proposed Power Efficient Clustering Scheme (PECS)


5- Numerical results


6- Conclusion


References

نمونه متن انگلیسی 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].

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