發(fā)布時(shí)間：2018-11-17 08:01

【摘要】：云計(jì)算由于其先進(jìn)的理念、方便的使用方式，越來越受到各大廠商和用戶的青睞。隨著云計(jì)算的廣泛使用，數(shù)據(jù)中心和集群的能耗問題越來越受到關(guān)注。 服務(wù)器目前消耗的能源已經(jīng)達(dá)到驚人的程度。大部分服務(wù)器在大部分時(shí)間內(nèi)都處于空閑狀態(tài)，這是對(duì)能源極大的浪費(fèi)。但是如果降低能耗，服務(wù)器性能也會(huì)降低，這是用戶所不愿意看到的。通常來說，云服務(wù)提供商和客戶之間會(huì)簽訂服務(wù)等級(jí)協(xié)議定義SLA（Service Level Agreement），規(guī)定了服務(wù)提供商提供服務(wù)的最低條件。為了降低數(shù)據(jù)中心的能源消耗和滿足服務(wù)等級(jí)協(xié)定（SLA）的要求，通常會(huì)在空閑時(shí)間關(guān)閉無用服務(wù)器。但是，服務(wù)器從關(guān)閉狀態(tài)回到工作狀態(tài)需要一定的時(shí)間。而在這一段時(shí)間內(nèi)，服務(wù)器的響應(yīng)時(shí)間可能會(huì)違反SLA的要求。 在這篇文章中，我們首先總結(jié)前人的能耗模型并進(jìn)行相應(yīng)的實(shí)驗(yàn)，提出了單機(jī)上的與CPU頻率和CPU利用率都相關(guān)的能耗模型。隨后我們利用排隊(duì)模型研究了集群上的服務(wù)器頻率、負(fù)載到達(dá)率和能耗之間的關(guān)系。發(fā)現(xiàn)服務(wù)器集群上也存在某一個(gè)負(fù)載下的最優(yōu)頻率，使得整個(gè)集群的能耗最少，同時(shí)SLA得到滿足。 隨著負(fù)載的變化，動(dòng)態(tài)的開關(guān)機(jī)或調(diào)整服務(wù)器的頻率，都是降低整個(gè)集群能耗的手段。如何在認(rèn)識(shí)到存在最優(yōu)頻率的基礎(chǔ)上有效結(jié)合這兩種手段，達(dá)到能耗最優(yōu)和滿足SLA的要求，是前人沒有的工作，本文繼續(xù)圍繞這一問題展開研究。在文獻(xiàn)[1]的基礎(chǔ)上，我們提出了Enhanced AutoScale （EAS）技術(shù)，該技術(shù)將最優(yōu)頻率作為一個(gè)重要參數(shù)加入到策略AutoScale中，也就是將開關(guān)機(jī)和CPU調(diào)頻調(diào)壓（DVFS）結(jié)合在一起。在EAS中，，調(diào)節(jié)頻率被用來彌補(bǔ)AutoScale中關(guān)機(jī)造成的性能損失。該論文提出了兩種EAS的實(shí)現(xiàn)方式，集中化的EAS（CEAS）和分布式的EAS （DEAS）。并給出了相應(yīng)的算法和具體實(shí)現(xiàn)。 實(shí)驗(yàn)結(jié)果表明這種方法能夠有效的降低響應(yīng)時(shí)間，同時(shí)只增加很少的能源消耗。我們的方法每瓦特性能（P P W）值在某些負(fù)載下甚至比AutoScale高了50%。
[Abstract]:Cloud computing is more and more popular among manufacturers and users because of its advanced concept and convenient way of use. With the wide use of cloud computing, the energy consumption of data centers and clusters has been paid more and more attention. Servers are currently consuming a staggering amount of energy. Most servers are idle most of the time, which is a great waste of energy. But if you reduce energy consumption, server performance will also be reduced, which users do not want to see. Typically, a service level agreement between a cloud service provider and a customer defines the SLA (Service Level Agreement), as a minimum condition for service delivery by a service provider. In order to reduce the energy consumption of the data center and meet the requirements of the Service level Agreement (SLA), useless servers are usually shut down during idle time. However, it takes some time for the server to return to work from shutdown. During this time, the server's response time may violate SLA's requirements. In this paper, we first summarize the previous energy consumption models and carry out corresponding experiments, and put forward the energy consumption model which is related to both CPU frequency and CPU utilization on a single machine. Then we use queuing model to study the relationship among server frequency, load arrival rate and energy consumption. It is found that there is an optimal frequency under a certain load on the server cluster, so that the energy consumption of the whole cluster is the least, and the SLA is satisfied. With the change of load, dynamic switching machine or adjusting the frequency of the server are the means to reduce the energy consumption of the whole cluster. How to effectively combine these two methods to achieve optimal energy consumption and meet the requirements of SLA on the basis of recognizing the existence of optimal frequency is a work that has not been done before. On the basis of reference [1], we propose the Enhanced AutoScale (EAS) technique, which adds the optimal frequency as an important parameter to the strategic AutoScale, that is, combining the switch machine with the CPU frequency modulation and voltage modulation (DVFS). In EAS, frequency regulation is used to compensate for performance losses caused by shutdown in AutoScale. This paper proposes two ways to implement EAS, centralized EAS (CEAS) and distributed EAS (DEAS). The corresponding algorithm and implementation are also given. Experimental results show that this method can effectively reduce the response time and increase only a small amount of energy consumption. Our method has a (P P W) value per watt that is even 50 per watt higher than AutoScale under some loads.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP368.5

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 王敬浩,黃叔懷;太極拳運(yùn)動(dòng)對(duì)高脂血癥合并Ⅱ型糖尿病患者的療效觀察及其機(jī)理探討[J];體育與科學(xué);2001年01期

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