本文選題：云計(jì)算 + 云服務(wù)　； 參考：《北京郵電大學(xué)》2014年博士論文

【摘要】：云計(jì)算作為一種新型的計(jì)算模式能夠以服務(wù)的形式按需向用戶提供彈性可擴(kuò)展的資源,從而大幅度提高資源利用率、降低信息服務(wù)成本。而云服務(wù)可靠提供的關(guān)鍵在于云服務(wù)的部署及維護(hù)管理,即如何為云服務(wù)合理分配資源以保證云服務(wù)的高效部署及可靠運(yùn)行。 然而,云服務(wù)部署中存在的用戶多樣性、基礎(chǔ)設(shè)施的海量異構(gòu)性等特點(diǎn),使得云計(jì)算平臺(簡稱云平臺)在云服務(wù)部署方面遇到了諸多挑戰(zhàn),例如,如何進(jìn)行虛擬鏡像的有效獲取、如何合理的分配資源,以及如何在服務(wù)器在線維護(hù)情況下執(zhí)行資源的動(dòng)態(tài)調(diào)整等。因此,針對上述問題,對云服務(wù)的部署與管理機(jī)制進(jìn)行了深入研究,具體研究內(nèi)容如下： (1)基于多點(diǎn)協(xié)作的虛擬鏡像文件高效獲取方法。針對在IaaS云按需型資源提供方式下,大尺寸虛擬機(jī)模板文件獲取耗時(shí)長導(dǎo)致的用戶虛擬機(jī)請求部署效率低下問題,提出了一種基于多點(diǎn)協(xié)作的虛擬鏡像文件動(dòng)態(tài)獲取方法。該方法首先根據(jù)數(shù)據(jù)中心鏡像文件的存儲位置及鏡像文件本身的特點(diǎn),設(shè)計(jì)一種混合分塊策略,用于將虛擬機(jī)模板文件劃分成細(xì)粒度的塊文件,然后,基于細(xì)粒度塊的本地緩存,提出了一種多點(diǎn)協(xié)作的虛擬機(jī)模板文件高效獲取方法,最后,仿真實(shí)驗(yàn)表明,該方法能夠快速響應(yīng)用戶所需的虛擬機(jī)模板文件請求,實(shí)現(xiàn)虛擬機(jī)的高效部署。 (2)基于應(yīng)用流友好的虛擬鏡像文件傳輸方法。針對在IaaS云預(yù)約型資源提供方式下,大尺寸虛擬鏡像文件傳輸給數(shù)據(jù)中心網(wǎng)絡(luò)造成大的額外網(wǎng)絡(luò)流量負(fù)載導(dǎo)致的數(shù)據(jù)中心應(yīng)用性能急劇下降問題,提出了一種應(yīng)用流友好的虛擬鏡像文件傳輸方法。該方法首先將隨時(shí)間變化的數(shù)據(jù)中心網(wǎng)絡(luò)建立在時(shí)間擴(kuò)展圖上,以虛擬模板文件傳輸給數(shù)據(jù)中心網(wǎng)絡(luò)帶來的負(fù)載影響最小為目標(biāo),建立時(shí)延容忍的虛擬機(jī)模板文件傳輸?shù)膯栴}求解模型,然后,針對該問題模型,采用遺傳優(yōu)化算法進(jìn)行最優(yōu)求解,最后,仿真實(shí)驗(yàn)表明,該方法能夠充分利用數(shù)據(jù)中心網(wǎng)絡(luò)上空閑的或是負(fù)載較輕的鏈路,為數(shù)據(jù)中心網(wǎng)絡(luò)上承載的各種應(yīng)用提供一個(gè)更為均衡的網(wǎng)絡(luò),從而減少大尺寸虛擬鏡像文件傳輸對數(shù)據(jù)中心網(wǎng)絡(luò)上承載的各種應(yīng)用的性能影響。 (3)面向負(fù)載均衡的虛擬網(wǎng)絡(luò)資源分配方法。針對虛擬網(wǎng)絡(luò)資源分配中物理路徑上中間節(jié)點(diǎn)資源瓶頸而導(dǎo)致后續(xù)虛擬網(wǎng)絡(luò)請求成功率降低問題,提出一種負(fù)載均衡的虛擬網(wǎng)絡(luò)資源分配方法。該方法首先考慮物理路徑上中間節(jié)點(diǎn)資源消耗,以節(jié)點(diǎn)負(fù)載和鏈路負(fù)載同時(shí)達(dá)到均衡為目標(biāo),將路徑跳數(shù)限制作為約束,建立虛擬網(wǎng)絡(luò)資源分配的問題求解模型,然后,針對該問題模型,采用多目標(biāo)負(fù)載均衡粒子群優(yōu)化算法求解,最后,仿真實(shí)驗(yàn)表明,該分配方法能夠有效消除資源瓶頸(為后續(xù)虛擬網(wǎng)絡(luò)請求提供了一個(gè)更為均衡的底層物理網(wǎng)絡(luò))從而提高虛擬網(wǎng)絡(luò)構(gòu)建成功率、網(wǎng)絡(luò)資源利用率以及基礎(chǔ)設(shè)施提供商的收益。 (4)服務(wù)器在線維護(hù)下通信成本感知的資源調(diào)整方法。針對數(shù)據(jù)中心服務(wù)器在線維護(hù)時(shí)虛擬機(jī)遷移而導(dǎo)致虛擬網(wǎng)絡(luò)通信開銷增加問題,提出了一種服務(wù)器在線維護(hù)下通信成本感知的資源調(diào)整方法。該方法首先找出服務(wù)器在線維護(hù)情況下虛擬機(jī)遷移策略的候選集,并以虛擬網(wǎng)絡(luò)中虛擬機(jī)之間的通信開銷最小為目標(biāo),以物理服務(wù)器的資源能力為約束,建立虛擬機(jī)遷移的問題求解模型,然后,針對該問題模型,采用模擬退火算法求解,最后,仿真實(shí)驗(yàn)表明,該調(diào)整方法能夠有效避免虛擬機(jī)由于服務(wù)器維護(hù)而造成的多次遷移,減少虛擬機(jī)遷移給網(wǎng)絡(luò)帶來的遷移流量開銷,減少多層應(yīng)用中虛擬機(jī)之間的通信開銷。
[Abstract]:As a new computing mode , cloud computing can provide users with flexible and scalable resources in the form of service , thereby greatly improving resource utilization rate and reducing information service cost . The key to reliable provision of cloud services lies in the deployment and maintenance management of cloud services , namely , how to allocate resources reasonably for cloud services to ensure efficient deployment and reliable operation of cloud services .

However , the cloud computing platform ( simply called the cloud platform ) meets many challenges in cloud service deployment , such as how to get effective acquisition of virtual mirror image , how to allocate resources reasonably and how to perform dynamic adjustment of resources under the condition of online maintenance of the server . Therefore , the deployment and management mechanism of cloud service is researched deeply , and the specific research contents are as follows :

The method comprises the following steps : firstly , according to the storage position of a data center image file and the characteristics of the image file , a mixed blocking strategy is designed to divide the virtual machine template file into a fine - grained block file , and finally , based on the local cache of the fine granularity block , a multi - point cooperative virtual machine template file high - efficiency acquisition method is proposed , and finally , the simulation experiment shows that the method can quickly respond to the request of the virtual machine template file required by the user and realize the efficient deployment of the virtual machine .

The invention relates to a virtual image file transmission method based on application flow friendliness , aiming at solving the problem that the data center application performance caused by large extra network traffic load caused by large - sized virtual image files to a data center network in the mode of providing a large - sized virtual image file to a data center network is extremely reduced .

The method comprises the following steps : firstly , taking into account the resource consumption of an intermediate node on the physical path , taking the node load and the link load as a target , solving a problem solving model of the virtual network resource allocation , and finally , aiming at the problem model , adopting a multi - target load balancing particle swarm optimization algorithm to solve the problem model , and finally , simulating experiment shows that the distribution method can effectively eliminate the resource bottleneck ( providing a more balanced bottom layer physical network for subsequent virtual network requests ) , thereby improving the success rate of the virtual network construction , the utilization rate of network resources and the benefits of the infrastructure providers .

The method comprises the following steps : firstly , finding a candidate set of a virtual machine migration policy under the condition of online maintenance of a data center server , establishing a candidate set of the virtual machine migration strategy under the condition of online maintenance of the server , establishing a problem solving model of the virtual machine migration by using the resource capacity of the physical server as a target , and finally , simulating an experiment to show that the adjusting method can effectively avoid the multiple migration caused by the maintenance of the virtual machine , reduce the migration flow cost caused by the migration of the virtual machine to the network , and reduce the communication cost between the virtual machines in the multi - layer application .
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TP393.09

【參考文獻(xiàn)】

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本文編號：2044254