【摘要】：云計(jì)算為數(shù)據(jù)中心帶來(lái)了機(jī)遇，也帶來(lái)了挑戰(zhàn)。云數(shù)據(jù)中心的資源需要得到合理的調(diào)度才能更高效地向用戶提供服務(wù)。物理服務(wù)器為了保持較高的性能，必須將CPU、內(nèi)存等的利用率保持在某個(gè)水平以下，因而需要均衡物理機(jī)之間的負(fù)載，盡量減少某些機(jī)器過(guò)載而另外一些機(jī)器空轉(zhuǎn)的情況。多數(shù)據(jù)中心環(huán)境下，數(shù)據(jù)中心要得到整體上較高的服務(wù)水平，也要盡量保持較低的資源利用率，因而在資源的數(shù)量一定時(shí)，均衡各數(shù)據(jù)中心之間的負(fù)載，有助于提高服務(wù)水平。 本文提出了多數(shù)據(jù)中心環(huán)境下云資源共享模型，并遵照該模型實(shí)現(xiàn)了云資源共享系統(tǒng)，詳細(xì)介紹了系統(tǒng)的設(shè)計(jì)和實(shí)現(xiàn)，包括系統(tǒng)主模塊設(shè)計(jì)、各模塊的通信機(jī)制、系統(tǒng)信息的保存方法等。之后，本文根據(jù)該系統(tǒng)所調(diào)度任務(wù)的考慮生命周期和資源共享的特點(diǎn)，提出了應(yīng)用于該模型的多數(shù)據(jù)中心負(fù)載均衡機(jī)制，包括離線和在線兩種方式的負(fù)載均衡算法。 最后，本文使用實(shí)驗(yàn)?zāi)M的方式將所提出的算法同輪詢、隨機(jī)、最小負(fù)載優(yōu)先、最長(zhǎng)處理時(shí)間優(yōu)先等經(jīng)典負(fù)載均衡算法進(jìn)行對(duì)比，驗(yàn)證所提出算法的性能。算法對(duì)比的指標(biāo)包括用戶的虛擬機(jī)任務(wù)請(qǐng)求拒絕個(gè)數(shù)、多個(gè)數(shù)據(jù)中心的整體不均衡度、最大的數(shù)據(jù)中心綜合利用率、最小的數(shù)據(jù)中心利用率與最大的數(shù)據(jù)中心綜合利用率之比等。實(shí)驗(yàn)數(shù)據(jù)顯示，本文所提出的算法與其它算法相比，在上述指標(biāo)方面有明顯的優(yōu)勢(shì)。
[Abstract]:Cloud computing brings both opportunities and challenges to data centers. The resources of cloud data center need to be scheduled reasonably to provide service to users more efficiently. In order to maintain high performance, the physical server must keep the utilization of CPU, memory below a certain level, so it is necessary to balance the load between the physical machines and minimize the overload of some machines and the idling of others. In the multi-data center environment, the data center should get a higher service level as a whole, but also maintain a low resource utilization rate. Therefore, when the number of resources is fixed, balancing the load between the data centers will help to improve the service level. In this paper, a cloud resource sharing model in multi-data center environment is proposed, and the cloud resource sharing system is implemented according to the model. The design and implementation of the system are introduced in detail, including the design of the main module of the system, the communication mechanism of each module. Methods of saving system information. Then, according to the characteristics of life cycle and resource sharing, this paper proposes a multi-data center load balancing mechanism for this model, including offline and online load balancing algorithms. Finally, the proposed algorithm is compared with the classical load balancing algorithms, such as polling, random, minimum load first and maximum processing time priority, in order to verify the performance of the proposed algorithm. The indexes of algorithm comparison include the number of requests rejected by the user's virtual machine task, the overall imbalance of multiple data centers, and the maximum comprehensive utilization ratio of data centers. The ratio of minimum data center utilization to maximum data center comprehensive utilization. Experimental data show that the proposed algorithm has obvious advantages over other algorithms.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP308

【參考文獻(xiàn)】

中國(guó)期刊全文數(shù)據(jù)庫(kù) 前2條

1 趙雷霆;;運(yùn)營(yíng)商級(jí)云計(jì)算數(shù)據(jù)中心發(fā)展研究[J];信息安全與技術(shù);2011年08期

2 周集良,彭小寧,王正華;基于集群的負(fù)載平衡調(diào)度算法研究與實(shí)現(xiàn)[J];計(jì)算機(jī)工程;2005年12期

中國(guó)博士學(xué)位論文全文數(shù)據(jù)庫(kù) 前4條

1 劉曉茜;云計(jì)算數(shù)據(jù)中心結(jié)構(gòu)及其調(diào)度機(jī)制研究[D];中國(guó)科學(xué)技術(shù)大學(xué);2011年

2 章文嵩;可伸縮網(wǎng)絡(luò)服務(wù)的研究與實(shí)現(xiàn)[D];中國(guó)人民解放軍國(guó)防科學(xué)技術(shù)大學(xué);2000年

3 王智明;云數(shù)據(jù)中心資源調(diào)度機(jī)制研究[D];北京郵電大學(xué);2012年

4 孫鑫;面向云環(huán)境數(shù)據(jù)中心的高效資源調(diào)度機(jī)制研究[D];北京郵電大學(xué);2012年

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本文編號(hào)：2297735