本文選題：數(shù)據(jù)中心 + 能耗最小化�。� 參考：《內(nèi)蒙古工業(yè)大學(xué)》2017年碩士論文

【摘要】：短短數(shù)年間,云計(jì)算技術(shù)從提出概念轉(zhuǎn)向大規(guī)模應(yīng)用。云計(jì)算技術(shù)可以與多種行業(yè)進(jìn)行融合,為用戶提供便捷的服務(wù),體現(xiàn)出巨大的應(yīng)用價(jià)值和發(fā)展前景。為了滿足對計(jì)算日益增長的需求,云服務(wù)提供商開始運(yùn)營不同規(guī)模的數(shù)據(jù)中心。與此同時(shí),數(shù)據(jù)中心消耗的能源也越來越多,逐漸成為制約云服務(wù)提供商發(fā)展的瓶頸,數(shù)據(jù)中心的能耗問題已經(jīng)吸引了工業(yè)界和學(xué)術(shù)界的關(guān)注,已成為研究的熱點(diǎn)。因此,以最小化數(shù)據(jù)中心能耗為目標(biāo)的資源控制策略是本文的主要研究內(nèi)容。首先,本文對數(shù)據(jù)中心的能耗最小化問題研究現(xiàn)狀進(jìn)行調(diào)研,主要包括數(shù)據(jù)中心能耗的分布和熱循環(huán)過程,服務(wù)器系統(tǒng)能耗研究現(xiàn)狀,制冷系統(tǒng)能耗研究現(xiàn)狀,以及目前數(shù)據(jù)中心能耗最小化的技術(shù)。同時(shí),本文還對數(shù)據(jù)中心能耗動(dòng)態(tài)優(yōu)化的理論——李雅普諾夫優(yōu)化理論進(jìn)行了研究,李雅普諾夫優(yōu)化理論中的離散時(shí)間隊(duì)列理論和偏移懲罰函數(shù)是研究的重點(diǎn)。隊(duì)列的穩(wěn)定性理論為期望均值約束條件提供了保證,李雅普諾夫偏移懲罰函數(shù)將隊(duì)列與成本函數(shù)相結(jié)合,使目標(biāo)函數(shù)找到性能和成本之間的平衡點(diǎn)。根據(jù)李雅普諾夫優(yōu)化理論設(shè)計(jì)的優(yōu)化算法能夠克服動(dòng)態(tài)優(yōu)化的不確定性與其求解算法計(jì)算復(fù)雜度高的不足,可以快速而準(zhǔn)確地選取決策變量,同時(shí)滿足約束條件,適用于優(yōu)化實(shí)地?cái)?shù)據(jù)中心的能源消耗。其次,本文對數(shù)據(jù)中心能耗最小化問題的模型進(jìn)行構(gòu)建,模型包括服務(wù)器能耗模型和制冷系統(tǒng)能耗模型,并形式化了服務(wù)質(zhì)量約束和服務(wù)器CPU平均溫度約束。以克服已有研究工作多數(shù)致力于僅降低服務(wù)器系統(tǒng)的能耗而忽略機(jī)房制冷系統(tǒng)的能耗,或沒有考慮到服務(wù)質(zhì)量(QoS,Quality of Service)約束和服務(wù)器CPU溫度約束的不足。然后,結(jié)合李雅普諾夫優(yōu)化理論中虛擬隊(duì)列的概念,本文推演了李雅普諾夫偏移函數(shù)的上界,并利用數(shù)據(jù)中心能耗最小化李雅普諾夫函數(shù)設(shè)計(jì)了線性控制策略和二次控制策略兩種能耗最小化控制策略。最后,本文使用數(shù)據(jù)中心真實(shí)工作負(fù)載數(shù)據(jù)進(jìn)行仿真,得到各項(xiàng)指標(biāo)的情況,并將設(shè)計(jì)的能耗最小化控制策略與基準(zhǔn)策略進(jìn)行比較,從數(shù)據(jù)和理論兩個(gè)方面對能耗最小化控制策略的性能進(jìn)行評價(jià),證明這兩種控制策略可以實(shí)現(xiàn)數(shù)據(jù)中心總能耗的最小化。并對實(shí)驗(yàn)結(jié)果做出討論,給出數(shù)據(jù)中心溫度感知能耗最小化問題的最優(yōu)解決方案。
[Abstract]:Within a few short years, cloud computing technology from the concept to large-scale applications. Cloud computing technology can be combined with a variety of industries to provide users with convenient services, reflecting a huge application value and development prospects. To meet the growing demand for computing, cloud service providers are operating data centers of different sizes. At the same time, more and more energy is consumed in the data center, which gradually becomes the bottleneck restricting the development of cloud service providers. The energy consumption of the data center has attracted the attention of industry and academia, and has become a hot research topic. Therefore, resource control strategy aiming at minimizing data center energy consumption is the main content of this paper. Firstly, this paper investigates the energy consumption minimization of data center, including the distribution of data center energy consumption and the process of thermal cycle, the research status of energy consumption in server system, and the research status of energy consumption in refrigeration system. And the current data center energy consumption minimization technology. At the same time, the Lyapunov optimization theory, which is the dynamic optimization theory of data center energy consumption, is also studied. The discrete time queue theory and offset penalty function in Lyapunov optimization theory are the key points of the research. The stability theory of the queue guarantees the expected mean constraint. The Lyapunov offset penalty function combines the queue with the cost function to make the objective function find the balance between performance and cost. The optimization algorithm designed according to Lyapunov optimization theory can overcome the uncertainty of dynamic optimization and the high computational complexity of its solution algorithm, and it can select the decision variables quickly and accurately, and satisfy the constraint conditions at the same time. Suitable for optimizing energy consumption in field data centers. Secondly, this paper constructs the model of data center energy minimization, including server energy consumption model and refrigeration system energy consumption model, and formalizes the QoS constraints and server CPU average temperature constraints. In order to overcome the shortcomings of most of the previous researches which only reduce the energy consumption of the server system and neglect the energy consumption of the refrigeration system in the computer room, or do not consider the QoS quality of Service constraint and the CPU temperature constraint of the server. Then, combined with the concept of virtual queue in Lyapunov optimization theory, the upper bound of Lyapunov migration function is deduced. The linear control strategy and the quadratic control strategy are designed by using the Lyapunov function to minimize the energy consumption of the data center. Finally, we use the real workload data of the data center to simulate, get the situation of each index, and compare the designed energy consumption minimization control strategy with the reference strategy. The performance of the energy consumption minimization control strategy is evaluated in terms of data and theory, and it is proved that these two control strategies can minimize the total energy consumption of the data center. The experimental results are discussed and the optimal solution to the problem of data center temperature sensing energy minimization is given.
【學(xué)位授予單位】：內(nèi)蒙古工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP308

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本文編號(hào)：1901528