کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
425161 685694 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Evaluating the cooling and computing energy demand of a datacentre with optimal server provisioning
ترجمه فارسی عنوان
ارزیابی تقاضای انرژی خنک کننده و محاسباتی از یک مرکز داده با تأمین بهینه سرور
کلمات کلیدی
محاسبات سبز؛ مرکز داده؛ سرورها؛ عملکرد و قابلیت اطمینان؛ اندازه گیری های انرژی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
چکیده انگلیسی


• Assessment of the temperature setpoint in datacentres’ energy consumption.
• Evaluation of cooling and computing factors with optimal server provisioning.
• Temperature-dependent redundancy with specific job service level objectives.
• Energy, temperature, and computing performance measurements from real servers.

As cloud computing continues to gain significance across fields, the energy consumption of datacentres creates new challenges in the design and operation of computer systems, with cooling remaining a key part of the total energy expenditure. We investigate the implications of increasing the room temperature setpoint in datacentres to save energy. For this, we develop a holistic model for the energy consumption of the server room that depends on user workload and service level agreement constraints, and that considers both cooling and computing energy dissipation. The model is applicable to a steady-state analysis of the system and brings insight into the impact of the most relevant parameters that affect the net energy consumption, such as the outside temperature, room temperature setpoint, and user demand. We analyse both static and dynamic server provisioning cases. In the latter case, a global power management scheme determines the optimal number of servers required to handle the incoming user demand to fulfil a target service level objective. Finally, we consider the extra energy needed to maintain service continuity under the expected higher server mortality rate due to warmer operational temperatures. Energy and temperature measurements acquired from a server machine running scientific benchmark programs allow to realistically fix model parameters for the study and to obtain pragmatic conclusions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Future Generation Computer Systems - Volume 57, April 2016, Pages 1–12
نویسندگان
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