本文選題：SaaS + 云�。� 參考：《山東大學(xué)》2014年碩士論文

【摘要】：隨著云計算發(fā)展,軟件開發(fā)作為一種服務(wù)已經(jīng)受到越來越多的關(guān)注。為了讓獨立軟件開發(fā)商(ISV)能夠?qū)⒕性诤诵臉I(yè)務(wù)應(yīng)用的開發(fā)上,更加方便、靈活、快捷地構(gòu)建SaaS系統(tǒng),平臺即服務(wù)(PaaS)理念因此發(fā)展起來。SaaS最大的優(yōu)點是將應(yīng)用在同一時間提供給多個租戶使用,并且一個租戶下可能有1個或者多個用戶,對租戶來說感覺不到其他租戶的存在。當(dāng)云計算快速發(fā)展,SaaS應(yīng)用交付平臺的數(shù)據(jù)正從單一的節(jié)點到多節(jié)點,數(shù)據(jù)量和租戶的數(shù)量呈指數(shù)增長,存儲在多個節(jié)點上的用戶數(shù)據(jù)均勻的分散在多個數(shù)據(jù)節(jié)點。 面對海量的數(shù)據(jù)和頻繁的并發(fā)訪問,將會給SaaS平臺帶來以下問題：(1)元數(shù)據(jù)存在單一的元數(shù)據(jù)節(jié)點上,所有數(shù)據(jù)節(jié)點使用的是同一份元數(shù)據(jù),元數(shù)據(jù)節(jié)點上硬件或者軟件若發(fā)生故障,則該元數(shù)據(jù)節(jié)點就不能完成任何數(shù)據(jù)的查詢工作了。用戶使用SaaS應(yīng)用時,無從獲取租戶定制信息,無法進行模式映射和SQL重寫,SaaS平臺將是不可用的。(2)租戶的資源需求是動態(tài)變化的,當(dāng)租戶需要的資源空間是隨著時間動態(tài)變化的且各個數(shù)據(jù)節(jié)點的負(fù)載不均衡下,就會出現(xiàn)熱點數(shù)據(jù),不僅元數(shù)據(jù)節(jié)點可能出現(xiàn)過載,數(shù)據(jù)節(jié)點也可能出現(xiàn)過載,那么租戶的SLA(Service-Level-Agreement)將得不到保障。 針對以上,本文基于SaaS應(yīng)用的特性,提出了支持?jǐn)?shù)據(jù)遷移的多租戶數(shù)據(jù)存儲模型,然后在此基礎(chǔ)上,提出了能夠識別租戶特性的云中多節(jié)點的SaaS平臺多租戶數(shù)據(jù)動態(tài)數(shù)據(jù)遷移算法。本文的主要工作如下： (1)提出了基于共享數(shù)據(jù)庫共享表模式下的云中SaaS應(yīng)用的多元數(shù)據(jù)節(jié)點模型。在共享SaaS多租戶數(shù)據(jù)存儲模式以及云中多個數(shù)據(jù)節(jié)點的基礎(chǔ)上,針對SaaS平臺單一元數(shù)據(jù)節(jié)點問題,提出了多元數(shù)據(jù)節(jié)點模型。模型中選取一個元數(shù)據(jù)節(jié)點作為元數(shù)據(jù)管理節(jié)點。闡述了模型中元數(shù)據(jù)結(jié)構(gòu),提出了SaaS平臺多元數(shù)據(jù)節(jié)點模型下,元數(shù)據(jù)分布策略,包括元數(shù)據(jù)劃分策略和基于分割定義的放置策略。并提出了基于分割訪問計數(shù)屬性等動態(tài)負(fù)載調(diào)整算法。該模型能有效解決單一元數(shù)據(jù)節(jié)點的失效、性能瓶頸、擴展性問題。 (2)提出了在云中多元數(shù)據(jù)節(jié)點模型基礎(chǔ)上的SaaS數(shù)據(jù)動態(tài)遷移策略。首先該策略考慮到多租戶的特征；其次,數(shù)據(jù)遷移是在線的,為了保證租戶對遷移中的數(shù)據(jù)能夠進行正常訪問,特別是正在進行遷移的源數(shù)據(jù)節(jié)點和目標(biāo)數(shù)據(jù)節(jié)點,本章提出了“單寫雙讀”的訪問模式,這樣不僅不會造成租戶訪問的中斷,還可以保證服務(wù)提供商許諾的SLA。最后,將傳統(tǒng)的兩階段提交的策略進行了擴展,保證數(shù)據(jù)一致性。該策略能夠?qū)⑦w移成本降至最低,能夠按照租戶數(shù)據(jù)的優(yōu)先級進行遷移,縮小每次遷移的數(shù)據(jù)量,節(jié)省網(wǎng)絡(luò)帶寬,防止SaaS平臺性能降低。文章最后我們給出“單寫雙讀”的多租戶數(shù)據(jù)訪問方式,保證遷移中數(shù)據(jù)的可用性和用戶訪問的不中斷性。
[Abstract]:With the development of cloud computing, software development as a service has received more and more attention. In order to enable independent software developer to focus on the development of core business applications, it is more convenient, flexible and fast to build SaaS system. The main advantage of the platform as a Service (Pasa) concept is that it can be used by more than one tenant at the same time, and there may be one or more users under one tenant, so the tenant can't feel the existence of other tenants. With the rapid development of cloud computing, the data of SaaS application delivery platform is changing from single node to multi-node, the amount of data and the number of tenants are increasing exponentially, and the user data stored on multiple nodes are distributed evenly across multiple data nodes. In the face of massive data and frequent concurrent access, it will bring the following problems to the SaaS platform: 1) metadata exists on a single metadata node, and all data nodes use the same metadata. If the hardware or software on the metadata node fails, the metadata node will not be able to complete any data query. When users use SaaS applications, there is no way to obtain tenant customization information, and no schema mapping and SQL rewriting on the SaaS platform will be unavailable. When the resource space needed by the tenant changes dynamically with time and the load of each data node is not balanced, there will be hot data, not only the metadata node may appear overload, but also the data node may appear overload. Then the tenant's SLA-Service-Level- Agreement will not be protected. In view of the above, based on the characteristics of SaaS application, a multi-tenant data storage model supporting data migration is proposed in this paper. This paper presents a dynamic data migration algorithm for multi-tenant data in SaaS platform based on multi-node cloud, which can recognize tenant characteristics. The main work of this paper is as follows: A multivariate data node model for cloud SaaS application based on shared database sharing table mode is proposed. On the basis of sharing SaaS multi-tenant data storage mode and multiple data nodes in the cloud, a multivariate data node model is proposed to solve the problem of single metadata node in SaaS platform. A metadata node is selected as the metadata management node in the model. In this paper, the metadata structure in the model is expounded, and the metadata distribution strategy under the multi-data node model of SaaS platform is proposed, including the metadata partition strategy and the placement strategy based on the partition definition. A dynamic load adjustment algorithm based on partitioned access counting attributes is proposed. The model can effectively solve the single metadata node failure, performance bottlenecks, scalability problems. (2) A dynamic migration strategy for SaaS data based on cloud multivariate data node model is proposed. Firstly, the strategy takes into account the characteristics of multi-tenant. Secondly, data migration is online to ensure that tenants can access the migrated data normally, especially the source data node and target data node that are migrating. This chapter proposes a "single write, double read" access mode, so that not only will not cause the tenant access disruption, but also guarantee the service provider promised slaa. Finally, the traditional two-phase submission strategy is extended to ensure data consistency. The strategy can reduce the migration cost to the minimum, can migrate according to the priority of tenant data, reduce the amount of data per migration, save network bandwidth, and prevent the performance of SaaS platform from being degraded. At the end of this paper, we give a multi-tenant data access mode of "single write and read" to ensure the availability of data in migration and the uninterrupted access of users.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.09;TP311.13

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本文編號：1900267