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網(wǎng)絡(luò )計算機模型下海量大數據存儲系統設計
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西安交通大學(xué) 城市學(xué)院

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TP333

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Under the network computer model mass big data storage system design
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    摘要:

    對網(wǎng)絡(luò )計算機模型下海量大數據進(jìn)行安全穩定的存儲,可以提高網(wǎng)絡(luò )計算機的使用價(jià)值,增加其使用周期。但目前的海量大數據存儲方法在存儲過(guò)程中,無(wú)法做到對其進(jìn)行靈活高效的存儲,存在大數據存儲分布密度較低,存儲開(kāi)銷(xiāo)較大等問(wèn)題。為此,以網(wǎng)絡(luò )計算機模型體系結構為基礎,提出了一種基于A(yíng)RM的海量大數據存儲系統設計方法。該設計方法先利用ARM芯片對網(wǎng)絡(luò )計算機模型下海量大數據存儲系統進(jìn)行硬件構造,將網(wǎng)絡(luò )海量大數據中的可利用與不可利用數據進(jìn)行分類(lèi)處理,采用VISA結構根據數據分類(lèi)結果對大數據存儲系統軟件部分進(jìn)行設計,依據大數據調度模型和存儲相似度特征對大數據存儲的時(shí)間,質(zhì)量等方面進(jìn)行計算,利用計算結果對大數據傳輸的閾值以及分布密度進(jìn)行記錄,最后根據循環(huán)分段的計算方式進(jìn)行冗余大數據特性壓縮,并對海量大數據的常規數據和冗余數據進(jìn)行存儲。實(shí)驗仿真證明,所提方法提高了海量大數據存儲的兼容性,增強了大數據存儲的精確性和靈活性。

    Abstract:

    The mass under the network computer models to security and stability of large data storage, can improve the use value of the network computer, increase its life cycle. But the current mass big data storage method in the process of storage, cannot afford to be flexible and efficient storage, there are large data storage distribution density is low, the problem such as storage overhead. To this end, on the basis of network computer system structure model, proposed a mass with large data storage system design method based on the ARM. Design method of the first use of ARM chips for mass big data storage system under the network computer model hardware structure, the network mass of big data available and cannot be classified by using data processing, USES the VISA structure according to the result of data classification was carried out on the big data storage system software part design, on the basis of large data scheduling model similarity characteristics of large data storage and storage time, quality, etc, to calculate, using the calculation results on the threshold of data transmission and distribution density of record, finally according to the calculation of circular section is redundant features large data compression, and the massive big data of conventional data and redundant data for storage. Experimental simulation show that the proposed method improves the compatibility of the mass big data storage, enhancing the accuracy and flexibility of the large data storage.

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古忻艷.網(wǎng)絡(luò )計算機模型下海量大數據存儲系統設計計算機測量與控制[J].,2017,25(6).

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  • 收稿日期:2017-03-18
  • 最后修改日期:2017-03-18
  • 錄用日期:2017-04-07
  • 在線(xiàn)發(fā)布日期: 2017-07-18
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