發(fā)布時間：2018-03-23 02:35

  本文選題：溯源信息　切入點：存儲系統　出處：《電子科技大學》2016年碩士論文　論文類型：學位論文

【摘要】：隨著云計算與大數據技術的迅速發(fā)展和應用,海量數據的存儲和管理問題成為人們關注的焦點,對數據存儲的靈活性、可擴展性以及并發(fā)性等都提出了更高的要求。眾多的互聯網應用使得多樣化的非結構化數據大量地產生,而傳統的關系型數據庫使用二維表來描述數據及數據之間的關系,因此它不適宜用于存儲靈活多變的非結構化數據。為滿足這些需求,許多新的存儲設備和存儲技術應運而生,例如SSD、NoSql、分布式存儲技術等,以適應非結構化數據應用場景,提高存儲和讀寫效率并盡量降低存儲成本。面對海量的數據,人們通常會關心某些數據的生命周期,例如它是何時被創(chuàng)建的、被哪些用戶使用過、存在多少副本等,這些信息對于數據管理、系統安全維護等來說有著十分重要的意義,通常也被稱為溯源信息。溯源信息描述了一個對象的歷史運動軌跡和動態(tài)衍生過程以及對象之間相互作用和推進的關系,隨著時間的推移,這些數據越來越龐大,對象之間的關系變得越來越復雜,因此如何有效地描述和存儲海量的溯源信息使得用戶可以簡單高效地對其進行存取,便是本文研究的核心。針對海量溯源信息的存儲問題,本文設計和實現了一個高性能溯源信息存儲系統DBPS(Double Buffer Provenance Store)。DBPS根據溯源信息的特點,在基于中心節(jié)點的分布式體系架構基礎上采取了多層次的存儲架構,包括緩存層和持久化存儲層。DBPS在緩存層采用了讀寫分離的雙緩存架構,設計了特定于溯源信息的數據存儲結構和索引,對溯源信息具有感知能力,在持久化存儲層它采用key-value數據庫作為底層的持久化存儲引擎,在提高數據的讀寫效率同時降低了存儲資源的消耗。與DBPS相比,大多數的溯源系統或溯源應用都直接使用關系型數據庫或圖形數據庫等現有的數據庫來存儲溯源信息,在讀寫溯源信息時需要對數據進行復雜的處理,讀寫效率較低。實驗結果表明,本文設計和實現的DBPS系統在創(chuàng)建和查詢溯源對象的數據時具有較高的效率,而在修改和刪除數據時效率相對較低,但在實際的應用中修改和刪除操作的使用頻率很低,因此使用DBPS來存取溯源信息的整體性能突出,能夠很好地滿足用戶的需求。
[Abstract]:With the rapid development and application of cloud computing and big data technology, the storage and management of massive data has become the focus of attention, the flexibility of data storage, Extensibility and concurrency are higher requirements. Many Internet applications make a variety of unstructured data generated in large quantities, while traditional relational databases use two-dimensional tables to describe the relationship between data and data. Therefore, it is not suitable for storing flexible and changeable unstructured data. In order to meet these requirements, many new storage devices and storage technologies have emerged, such as SSDN NoSql, distributed storage technology and so on, in order to adapt to unstructured data application scenarios. People usually care about the life cycle of certain data, such as when it is created, who has used it, how many copies it is, and so on. This information is of great significance to data management, system security maintenance, etc. Also known as traceability information. Traceability information describes an object's historical trajectory and dynamic derivation process, as well as the interaction and advancement of objects, and these data grow larger and larger over time. The relationship between objects becomes more and more complex, so how to effectively describe and store massive traceability information to enable users to easily and efficiently access it is the core of this paper. In this paper, a high performance traceability information storage system DBPS(Double Buffer Provenance Store).DBPS is designed and implemented. According to the characteristics of traceability information, a multi-layer storage architecture is adopted based on the distributed architecture based on central node. The cache layer and the persistent storage layer. DBPS adopts the dual cache architecture of read-write separation in the cache layer, designs the data storage structure and index specific to traceability information, and has the ability to perceive the traceability information. In the persistent storage layer, key-value database is used as the underlying persistent storage engine, which improves the efficiency of data reading and writing and reduces the consumption of storage resources. Most traceability systems or applications directly use existing databases such as relational databases or graphic databases to store traceability information, which requires complex processing when reading and writing traceability information. The experimental results show that the DBPS system designed and implemented in this paper has a high efficiency in creating and querying the data of traceability objects, but in modifying and deleting the data, the efficiency is relatively low. However, the frequency of modifying and deleting operations is very low in practical applications, so the overall performance of using DBPS to access traceability information is outstanding and can meet the needs of users.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP333

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本文編號：1651551