本文選題：SaaS + 放置與訪問��； 參考：《山東大學(xué)》2014年碩士論文

【摘要】：伴隨多租賃理念在業(yè)界的推廣應(yīng)用,基于SaaS模式的應(yīng)用已經(jīng)成為一種高效、先進(jìn)的業(yè)務(wù)應(yīng)用解決方案。單實(shí)例多租賃(Single Instance Multi-tenancy)的應(yīng)用模式體現(xiàn)出其低費(fèi)用,低維護(hù),高效應(yīng)用的特點(diǎn)；SaaS應(yīng)用的軟件提供商,為了能夠提供更好的軟件服務(wù),對(duì)部署的應(yīng)用服務(wù)SLA有了更高的要求,而云計(jì)算的出現(xiàn),恰恰能夠提供高可用的系統(tǒng)應(yīng)用和高擴(kuò)展的應(yīng)用部署和數(shù)據(jù)服務(wù)。 面對(duì)共享架構(gòu)共享存儲(chǔ)的云數(shù)據(jù)SaaS應(yīng)用,多租戶數(shù)據(jù)被放置到云中多個(gè)數(shù)據(jù)節(jié)點(diǎn)上,而隨機(jī)或者不合理選取云數(shù)據(jù)節(jié)點(diǎn)進(jìn)行放置,容易引發(fā)應(yīng)用數(shù)據(jù)節(jié)點(diǎn)的負(fù)載不均衡,同時(shí)也可能會(huì)增加租戶數(shù)據(jù)訪問及副本一致性更新的代價(jià)；針對(duì)云中多租戶數(shù)據(jù)訪問,結(jié)合多租戶和云存儲(chǔ)特點(diǎn),如何實(shí)現(xiàn)多租戶數(shù)據(jù)應(yīng)用請(qǐng)求訪問與合理調(diào)度策略,從而來降低節(jié)點(diǎn)負(fù)載并保持節(jié)點(diǎn)間負(fù)載均衡,實(shí)現(xiàn)系統(tǒng)的高效穩(wěn)定運(yùn)行。 面對(duì)這些問題,本文設(shè)計(jì)了多租戶云平臺(tái)系統(tǒng)存儲(chǔ)架構(gòu)模型,在此存儲(chǔ)模型的基礎(chǔ)之上,提出了多租戶數(shù)據(jù)放置與訪問的目標(biāo)與解決方案,主要貢獻(xiàn)如下： 1、針對(duì)隨機(jī)或不合理的云數(shù)據(jù)放置,導(dǎo)致數(shù)據(jù)節(jié)點(diǎn)負(fù)載不均衡問題,設(shè)計(jì)多租戶數(shù)據(jù)放置與訪問算法,獲得最優(yōu)的多租戶數(shù)據(jù)放置與訪問策略。 通過引入多租戶數(shù)據(jù)放置權(quán)重函數(shù),構(gòu)建多租戶數(shù)據(jù)放置與訪問模型,利用圖算法理論,提出了基于節(jié)點(diǎn)網(wǎng)絡(luò)距離和數(shù)據(jù)負(fù)載的數(shù)據(jù)放置與訪問算法,實(shí)現(xiàn)了基于圖的最優(yōu)完全圖的放置與訪問算法,并對(duì)算法進(jìn)行正確性和復(fù)雜性的分析,保證了數(shù)據(jù)的合理放置和節(jié)點(diǎn)的負(fù)載均衡,減小租戶數(shù)據(jù)訪問及副本一致性更新的代價(jià)。 2、針對(duì)云中多租戶數(shù)據(jù)訪問,設(shè)計(jì)多租戶數(shù)據(jù)訪問請(qǐng)求處理功能與流程,實(shí)現(xiàn)了面向云中多租戶的數(shù)據(jù)虛擬化訪問。 通過提出面向云中多租戶的數(shù)據(jù)請(qǐng)求訪問模型,設(shè)計(jì)了云中多租戶數(shù)據(jù)的訪問請(qǐng)求目標(biāo),針對(duì)不同租戶類型和訪問數(shù)據(jù)類型的,詳細(xì)描述云中多租戶數(shù)據(jù)訪問處理流程,實(shí)現(xiàn)根據(jù)多租戶元數(shù)據(jù)、業(yè)務(wù)數(shù)據(jù)等不同數(shù)據(jù)類型的多租戶數(shù)據(jù)訪問請(qǐng)求處理。 3、面對(duì)云中多數(shù)據(jù)節(jié)點(diǎn)請(qǐng)求訪問與數(shù)據(jù)不一致性問題,利用多租戶數(shù)據(jù)放置與訪問模型和算法,提出根據(jù)節(jié)點(diǎn)負(fù)載狀態(tài)的動(dòng)態(tài)調(diào)度訪問模型,實(shí)現(xiàn)多租戶數(shù)據(jù)的高效訪問；借鑒Paxos算法,結(jié)合多租戶元數(shù)據(jù)和多租戶特點(diǎn)進(jìn)行改進(jìn),引入元數(shù)據(jù)描述隊(duì)列的數(shù)據(jù)結(jié)構(gòu),解決云中多租戶數(shù)據(jù)可能出現(xiàn)的數(shù)據(jù)不一致的問題,保證SaaS應(yīng)用系統(tǒng)的可用性。 結(jié)合文中提出的多租戶數(shù)據(jù)放置與訪問模型與算法,本文通過實(shí)驗(yàn)評(píng)估證明了多租戶數(shù)據(jù)放置的正確性和動(dòng)態(tài)調(diào)度訪問的有效性；文中提出的模型與策略在一定程度上不僅可以提高租戶之間的共享程度、改進(jìn)數(shù)據(jù)放置的負(fù)載均衡,而且可以減輕數(shù)據(jù)副本更新的時(shí)間,減少租戶訪問數(shù)據(jù)的代價(jià),為云中SaaS數(shù)據(jù)管理與應(yīng)用提供了參考與幫助。
[Abstract]:With the application of multi - tenancy concept in the industry , the application of the SaaS model has become an efficient and advanced business application solution . The application mode of Single Instance Multi - tenancy ( Single Instance Multi - tenancy ) shows its low cost , low maintenance and high efficiency application .
SaaS - based software providers , in order to provide better software services , have higher requirements for deployed application service SLAs , while cloud computing is emerging to provide highly available system applications and highly scalable application deployment and data services .

Facing the cloud data SaaS application shared by the shared architecture , the multi - tenant data is placed on a plurality of data nodes in the cloud , and the cloud data nodes are randomly or unreasonably selected to be placed , the load of the application data node is easily caused to be unbalanced , and meanwhile , the cost of the tenant data access and the copy consistency update may be increased ;
Aiming at multi - tenant data access in the cloud , combining the characteristics of multi - tenancy and cloud storage , how to realize multi - tenant data application request access and reasonable scheduling strategy can be realized , so that the node load can be reduced and the load balance among nodes is maintained , and the efficient and stable operation of the system is realized .

In the face of these problems , this paper designs a multi - tenant cloud platform system storage architecture model , based on this storage model , puts forward the target and solution of multi - tenant data placement and access , and the main contribution is as follows :

1 . Aiming at random or unreasonable cloud data placement , the data node load imbalance problem is caused , and the multi - tenant data placement and access algorithm is designed to obtain the optimal multi - tenant data placement and access strategy .

By introducing a multi - tenant data placement weight function , a multi - tenant data placement and access model is constructed . Based on the theory of graph algorithm , a data placement and access algorithm based on node network distance and data load is proposed , the placement and access algorithm of the optimal complete graph based on the graph is realized , the correctness and complexity of the algorithm are analyzed , the reasonable placement of the data and the load balance of the nodes are guaranteed , and the cost of the tenant data access and the copy consistency update is reduced .

2 . For multi - tenant data access in the cloud , the multi - tenant data access request processing function and the process are designed , and the data virtualization access for multi - tenant in the cloud is realized .

According to the data request access model for multi - tenant in the cloud , the access request target of multi - tenant data in the cloud is designed , and the multi - tenant data access processing flow of multi - tenant data in the cloud is described in detail aiming at different tenant types and access data types , and multi - tenant data access request processing according to different data types such as multi - tenant metadata and service data is realized .

3 , facing the problem of request access and data inconsistency of the multi - tenant data node in the cloud , using the multi - tenant data placement and access model and the algorithm , and putting forward the dynamic scheduling access model according to the node load state to realize the efficient access of the multi - tenant data ;
This paper introduces the data structure of multi - tenant metadata and multi - tenancy , introduces the data structure of metadata description queue , and solves the problem of inconsistent data of multi - tenant data in the cloud , and ensures the availability of SaaS application system .

Based on the multi - tenant data placement and access model and algorithm proposed in the paper , the correctness of multi - tenant data placement and the validity of dynamic scheduling access are proved through experimental evaluation .
The proposed model and strategy can not only improve the sharing degree among tenants , improve the load balance of data placement , but also reduce the time of data copy update , reduce the cost of tenant access data , and provide reference and help for SaaS data management and application in the cloud .

【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.09

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本文編號(hào)：1846246