本文選題：綠色計(jì)算 + 云計(jì)算��； 參考：《南京郵電大學(xué)》2014年碩士論文

【摘要】：隨著云計(jì)算技術(shù)的迅速發(fā)展，使得云數(shù)據(jù)中心服務(wù)器的規(guī)模每年都在不斷的擴(kuò)大，產(chǎn)生巨大的能源開(kāi)銷(xiāo)。不合理的調(diào)度策略同樣導(dǎo)致能源浪費(fèi)嚴(yán)重，使得云數(shù)據(jù)中心的運(yùn)營(yíng)成本不斷增加。因此，綠色云計(jì)算的概念應(yīng)運(yùn)而生。針對(duì)目前云數(shù)據(jù)中心的高能耗、低效率問(wèn)題，，本文圍繞著綠色云計(jì)算系統(tǒng)模型的構(gòu)建、資源配置和任務(wù)調(diào)度算法的設(shè)計(jì)及驗(yàn)證等工作展開(kāi)了一系列的研究與探索，主要包括： 首先，從實(shí)現(xiàn)綠色云計(jì)算的內(nèi)部和外部因素出發(fā)，設(shè)計(jì)了一種高效可靠的綠色云計(jì)算系統(tǒng)模型。該模型重點(diǎn)著手于系統(tǒng)內(nèi)部的資源配置模塊和任務(wù)調(diào)度模塊，針對(duì)這兩個(gè)子模塊的實(shí)際需求，給出了具體的實(shí)施方案。資源配置模塊使得系統(tǒng)資源的分配更加合理，提高了系統(tǒng)資源的利用率，降低了云計(jì)算系統(tǒng)整體的能源消耗；任務(wù)調(diào)度模塊能夠保證云計(jì)算系統(tǒng)具有合理的任務(wù)調(diào)度機(jī)制。 其次，從全局角度出發(fā)，抽象任務(wù)調(diào)度問(wèn)題為資源配置問(wèn)題。通過(guò)預(yù)測(cè)用戶(hù)請(qǐng)求的負(fù)載大小，并結(jié)合當(dāng)前系統(tǒng)狀態(tài)和資源分布，采取保守控制策略，計(jì)算下一個(gè)周期內(nèi)任務(wù)對(duì)系統(tǒng)資源的需求量。然后，建立滿(mǎn)足多目標(biāo)約束的能耗模型，提出基于概率匹配的資源配置算法，實(shí)現(xiàn)低能耗資源配置。在此基礎(chǔ)上，提出基于改進(jìn)型模擬退火的資源配置算法，進(jìn)一步降低系統(tǒng)能耗。實(shí)驗(yàn)結(jié)果表明，采取的預(yù)測(cè)與控制策略能夠有效避免資源配置滯后于用戶(hù)請(qǐng)求的問(wèn)題，提高系統(tǒng)的響應(yīng)比和穩(wěn)定性；提出的資源配置算法能夠激活更少主機(jī)，實(shí)現(xiàn)激活主機(jī)集合之間更好的負(fù)載均衡和資源的最大化利用，降低云計(jì)算系統(tǒng)能耗。 最后，為了設(shè)計(jì)合理的任務(wù)調(diào)度機(jī)制，提出一種面向云計(jì)算平臺(tái)任務(wù)調(diào)度的多級(jí)負(fù)載評(píng)估方法。該方法為綠色云計(jì)算系統(tǒng)的任務(wù)調(diào)度提供一種合理的負(fù)載評(píng)估方法。在此基礎(chǔ)上，提出一種基于動(dòng)態(tài)負(fù)載調(diào)節(jié)的自適應(yīng)云計(jì)算任務(wù)調(diào)度策略，任務(wù)節(jié)點(diǎn)能夠自適應(yīng)負(fù)載的變化，按照計(jì)算能力獲取任務(wù)，實(shí)現(xiàn)各個(gè)節(jié)點(diǎn)自調(diào)節(jié)，同時(shí)避免因采用復(fù)雜的調(diào)度算法，使得管理節(jié)點(diǎn)承載巨大的系統(tǒng)開(kāi)銷(xiāo)，成為系統(tǒng)性能瓶頸。實(shí)驗(yàn)結(jié)果表明，基于動(dòng)態(tài)負(fù)載調(diào)節(jié)的自適應(yīng)云計(jì)算任務(wù)調(diào)度策略高效可靠，適用于異構(gòu)云計(jì)算集群的計(jì)算環(huán)境，性能優(yōu)于現(xiàn)有的任務(wù)調(diào)度策略。
[Abstract]:With the rapid development of cloud computing technology, the scale of cloud data center server is expanding every year, which brings huge energy cost. Unreasonable scheduling strategy also leads to serious energy waste, which makes the operating cost of cloud data center increasing. Therefore, the concept of green cloud computing came into being. Aiming at the problem of high energy consumption and low efficiency in cloud data center, this paper focuses on the construction of green cloud computing system model, the design and verification of resource allocation and task scheduling algorithm, etc. Firstly, an efficient and reliable green cloud computing system model is designed based on the internal and external factors of green cloud computing. The model focuses on the resource allocation module and task scheduling module in the system. According to the actual requirements of the two sub-modules, the concrete implementation scheme is given. Resource allocation module makes the allocation of system resources more reasonable, improves the utilization of system resources, and reduces the overall energy consumption of cloud computing system. Task scheduling module can ensure that cloud computing system has a reasonable task scheduling mechanism. Secondly, from the global point of view, the abstract task scheduling problem is a resource allocation problem. By predicting the load size of the user request and combining the current system status and resource distribution, conservative control strategy is adopted to calculate the demand for system resources for the next cycle. Then, the energy consumption model satisfying multi-objective constraints is established, and a resource allocation algorithm based on probability matching is proposed to achieve low energy resource allocation. On this basis, a resource allocation algorithm based on improved simulated annealing is proposed to further reduce the energy consumption of the system. Experimental results show that the proposed prediction and control strategy can effectively avoid the problem of resource allocation lagging behind user requests, improve the response ratio and stability of the system, and the proposed resource allocation algorithm can activate fewer hosts. In order to reduce the energy consumption of cloud computing systems, better load balance and maximum utilization of resources can be achieved between the active host sets. Finally, in order to design a reasonable task scheduling mechanism, a multi-level load assessment method for task scheduling in cloud computing platform is proposed. This method provides a reasonable load assessment method for task scheduling of green cloud computing systems. On this basis, an adaptive cloud computing task scheduling strategy based on dynamic load regulation is proposed. The task node can adapt the load change, acquire the task according to the computing power, and realize the self-adjustment of each node. At the same time, it is avoided that the management node carries huge system overhead and becomes the bottleneck of system performance because of the use of complex scheduling algorithm. The experimental results show that the adaptive cloud computing task scheduling strategy based on dynamic load regulation is efficient and reliable, and it is suitable for computing environment of heterogeneous cloud computing cluster, and its performance is superior to the existing task scheduling strategy.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TP393.01

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