云計算中虛擬機(jī)節(jié)能調(diào)度機(jī)制研究
發(fā)布時間：2018-08-09 16:48
【摘要】：云計算的出現(xiàn)給當(dāng)代信息產(chǎn)業(yè)帶來一場變革，通過按需付費(fèi)的服務(wù)模式，云計算能夠提供靈活的按需供給的計算資源服務(wù)。隨著云計算的發(fā)展，世界各地都建立起了包含數(shù)千計算節(jié)點(diǎn)的大型云數(shù)據(jù)中心。然而，數(shù)據(jù)中心需要消耗大量的能源，這不僅增加了云服務(wù)提供商的運(yùn)營成本，而且產(chǎn)生了大量的二氧化碳排放，對環(huán)境造成了污染。 目前，數(shù)據(jù)中心利用虛擬機(jī)動態(tài)遷移技術(shù)，對用戶資源進(jìn)行整合，能夠有效提高資源利用率、降低能耗。但同時，虛擬機(jī)在整合過程中會發(fā)生服務(wù)器主機(jī)過載的現(xiàn)象，導(dǎo)致服務(wù)性能降低，影響用戶的服務(wù)質(zhì)量，甚至?xí)o云服務(wù)提供商帶來巨大的經(jīng)濟(jì)損失。 針對上述問題，本研究提出了一種云環(huán)境中虛擬機(jī)節(jié)能調(diào)度啟發(fā)式算法，該算法綜合考慮了能量消耗和用戶服務(wù)質(zhì)量兩方面因素，通過虛擬機(jī)整合，提高計算資源的利用率，從而降低數(shù)據(jù)中心的能耗狀況，減少碳排放。同時該算法將戶服務(wù)等級協(xié)議(Service Level Agreement, SLA)的違反率保持在較低的水平，，從而保證了用戶的服務(wù)質(zhì)量。本文主要研究工作和成果如下： 首先，本課題中虛擬機(jī)節(jié)能調(diào)度算法分為四個部分：主機(jī)過載檢測、主機(jī)低負(fù)載檢測、虛擬機(jī)選擇以及主機(jī)選擇。在主機(jī)過載檢測的步驟中，通過分析主機(jī)過載時，虛擬機(jī)動態(tài)遷移引起的能耗變化狀況，得出一種虛擬機(jī)遷移的啟發(fā)式策略。 其次，運(yùn)用前面得出的啟發(fā)式策略提出了一種虛擬機(jī)節(jié)能調(diào)度算法，該算法對虛擬機(jī)的負(fù)載進(jìn)行預(yù)測，從而對主機(jī)的過載情況進(jìn)行判定，進(jìn)而實行虛擬機(jī)的節(jié)能調(diào)度。 最后，通過采集虛擬機(jī)負(fù)載的真實數(shù)據(jù)，在CloudSim云模擬平臺中對本課題算法進(jìn)行了對比實驗分析。實驗結(jié)果表明，該算法能夠有效的降低數(shù)據(jù)中心能耗，同時將SLA的違反率保持在降低的水平，取得了較好的效果。
[Abstract]:The emergence of cloud computing has brought a revolution to the modern information industry. Through the on-demand service model, cloud computing can provide flexible on-demand computing resources services. With the development of cloud computing, large cloud data centers with thousands of computing nodes have been established all over the world. However, data centers consume a lot of energy, which not only increases the operating costs of cloud service providers, but also produces a lot of carbon dioxide emissions, which pollutes the environment. At present, using virtual machine dynamic migration technology to integrate user resources, data center can effectively improve resource utilization and reduce energy consumption. But at the same time, the virtual machine in the process of integration will occur server host overload phenomenon, resulting in service performance degradation, affect the quality of service of users, and even bring huge economic losses to cloud service providers. In order to solve the above problems, a heuristic algorithm of virtual machine energy saving scheduling in cloud environment is proposed in this paper. This algorithm considers both energy consumption and user service quality, and improves the utilization ratio of computing resources through virtual machine integration. Thus reducing the energy consumption of the data center, reducing carbon emissions. At the same time, the algorithm keeps the violation rate of (Service Level Agreement, SLA) at a low level, thus ensuring the quality of service of the user. The main research work and results are as follows: firstly, the virtual machine energy-saving scheduling algorithm is divided into four parts: host overload detection, host low load detection, virtual machine selection and host selection. In the process of host overload detection, a heuristic strategy of virtual machine migration is proposed by analyzing the energy consumption change caused by virtual machine dynamic migration when the host is overloaded. Secondly, using the heuristic strategy, a virtual machine energy-saving scheduling algorithm is proposed, which predicts the load of the virtual machine, and then determines the overload of the host, and then implements the energy-saving scheduling of the virtual machine. Finally, by collecting the real data of virtual machine load, the algorithm is compared and analyzed in CloudSim cloud simulation platform. The experimental results show that the proposed algorithm can effectively reduce the energy consumption of the data center, while keeping the SLA violation rate at the reduced level, and achieves good results.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP302
本文編號：2174707
[Abstract]:The emergence of cloud computing has brought a revolution to the modern information industry. Through the on-demand service model, cloud computing can provide flexible on-demand computing resources services. With the development of cloud computing, large cloud data centers with thousands of computing nodes have been established all over the world. However, data centers consume a lot of energy, which not only increases the operating costs of cloud service providers, but also produces a lot of carbon dioxide emissions, which pollutes the environment. At present, using virtual machine dynamic migration technology to integrate user resources, data center can effectively improve resource utilization and reduce energy consumption. But at the same time, the virtual machine in the process of integration will occur server host overload phenomenon, resulting in service performance degradation, affect the quality of service of users, and even bring huge economic losses to cloud service providers. In order to solve the above problems, a heuristic algorithm of virtual machine energy saving scheduling in cloud environment is proposed in this paper. This algorithm considers both energy consumption and user service quality, and improves the utilization ratio of computing resources through virtual machine integration. Thus reducing the energy consumption of the data center, reducing carbon emissions. At the same time, the algorithm keeps the violation rate of (Service Level Agreement, SLA) at a low level, thus ensuring the quality of service of the user. The main research work and results are as follows: firstly, the virtual machine energy-saving scheduling algorithm is divided into four parts: host overload detection, host low load detection, virtual machine selection and host selection. In the process of host overload detection, a heuristic strategy of virtual machine migration is proposed by analyzing the energy consumption change caused by virtual machine dynamic migration when the host is overloaded. Secondly, using the heuristic strategy, a virtual machine energy-saving scheduling algorithm is proposed, which predicts the load of the virtual machine, and then determines the overload of the host, and then implements the energy-saving scheduling of the virtual machine. Finally, by collecting the real data of virtual machine load, the algorithm is compared and analyzed in CloudSim cloud simulation platform. The experimental results show that the proposed algorithm can effectively reduce the energy consumption of the data center, while keeping the SLA violation rate at the reduced level, and achieves good results.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP302
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本文編號：2174707
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