云计算环境下不可靠数据恢复方法研究
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摘要
由于云计算环境下不可靠数据中包含有利用价值的信息,但直接使用可能会给计算机带来负担,所以需要对云计算环境下不可靠数据进行恢复;当前大多数方法对不可靠数据进行复写时,利用地址映射层分配新的写入地址,因此不可靠的数据在一段时间内仍存在于云存储中,在这样的系统上实现对其的保护,不需额外保存数据的更新信息;通过FLASH的带外区记录时间戳,在FTL的映射项中增加时间戳信息,在不跟踪映射表每次更新的情况下,达到数据快速恢复的目的;但这种方法对云存储系统性能产生不利影响;为此,提出一种基于张量Tucker阈值的云计算环境下不可靠数据恢复方法,首先利用云计算环境下节点自身的随机秘钥生成器产生随机会话密钥,并对不可靠数据HMAC报文鉴别码进行计算,从而实现保护和重构;在此基础上,将不可靠数据的阈值分解过程与奇异阈值方法相结合,从而得到Tncker阈值算子,实现动态的数据恢复,恢复过程中利用Tucker阈值算子与增广拉格朗日乘子方法相结合的方式选择n-秩相似张量,提出基于增广拉格朗日乘子方法的不可靠数据Tucker阈值恢复方法,完成云计算环境下不可靠数据恢复;实验证明,所提方法能够有效提高不可靠数据恢复的准确性,降低数据恢复的能耗和时间,具有较强的可行性,为该课题的应用研究提供理论依据。
Because the cloud computing environment is unreliable and the data contain valuable information,the direct use may lead to the burden on the computer,so it is necessary to recover the unreliable data in the cloud computing environment.Most of the current methods of copying unreliable data,use the address mapping layer assignment write new address,so unreliable data in a period of time still exists in the cloud storage,the protection is achieved in such a system,do not need to update the channel additional data storage information.The timestamp information is added to the mapping term of FTL through the outer zone record timestamp of FLASH,and the fast recovery of data is achieved without updating the mapping table each time.But this approach has a detrimental effect on the performance of cloud storage systems.Therefore,this paper proposes a method to calculate environment unreliable data recovery method based on tensor Tucker threshold cloud,first calculate the random secret key generator node environment generates a random session key using the cloud,and the unreliable data HMAC message authentication code is calculated,so as to realize the protection and reconstruction.On this basis,combining the unreliable data threshold decomposition process and singular threshold method,in order to get the threshold of Tncker operator,to achieve dynamic data recovery,similar n-rank tensor combined with Tucker threshold operator and the recovery process using augmented Lagrange multiplier method is chosen,no reliable data recovery method of Tucker threshold augmented Lagrange multiplier based on the proposed,completed under the cloud computing environment is not reliable data recovery.Experimental results show that the proposed method can effectively improve the accuracy of unreliable data recovery,reduce the energy consumption and time of data restoration,and has a strong feasibility.It provides a theoretical basis for the application of this topic.
Because the cloud computing environment is unreliable and the data contain valuable information,the direct use may lead to the burden on the computer,so it is necessary to recover the unreliable data in the cloud computing environment.Most of the current methods of copying unreliable data,use the address mapping layer assignment write new address,so unreliable data in a period of time still exists in the cloud storage,the protection is achieved in such a system,do not need to update the channel additional data storage information.The timestamp information is added to the mapping term of FTL through the outer zone record timestamp of FLASH,and the fast recovery of data is achieved without updating the mapping table each time.But this approach has a detrimental effect on the performance of cloud storage systems.Therefore,this paper proposes a method to calculate environment unreliable data recovery method based on tensor Tucker threshold cloud,first calculate the random secret key generator node environment generates a random session key using the cloud,and the unreliable data HMAC message authentication code is calculated,so as to realize the protection and reconstruction.On this basis,combining the unreliable data threshold decomposition process and singular threshold method,in order to get the threshold of Tncker operator,to achieve dynamic data recovery,similar n-rank tensor combined with Tucker threshold operator and the recovery process using augmented Lagrange multiplier method is chosen,no reliable data recovery method of Tucker threshold augmented Lagrange multiplier based on the proposed,completed under the cloud computing environment is not reliable data recovery.Experimental results show that the proposed method can effectively improve the accuracy of unreliable data recovery,reduce the energy consumption and time of data restoration,and has a strong feasibility.It provides a theoretical basis for the application of this topic.
引文
[1]张露,尚艳玲.云计算环境下资源调度系统设计与实现[J].计算机测量与控制,2017,25(1):131-134.
[2]周虹,陈锋.一种云计算共享数据完整性公开审计方案[J].电子设计工程,2016,24(9):60-62.
[3]崔立鲁,朱贵发.利用重力卫星数据恢复地球质量迁移方法的研究[J].科学技术与工程,2015,15(14):106-109.
[4]向劲松,王举,吴涛,等.基于脉冲展宽波形的光脉冲位置调制异步采样信号的数据恢复技术[J].光学学报,2017(1):74-81.
[5]韩利华,程聪.遮挡物体的图像恢复方法研究与仿真[J].计算机仿真,2016,33(11):345-348.
[6]刘金明,谢秋菊,王雪,等.基于GSA-SVM的畜禽舍废气监测缺失数据恢复方法[J].东北农业大学学报,2015,46(5):95-101.
[7]杨立东,王晶,谢湘,等.基于低秩张量补全的多声道音频信号恢复方法[J].电子与信息学报,2016,38(2):394-399.
[8]白晋国,孙红胜,胡泽明.一种基于SQLite3文件格式的删除数据恢复方法[J].小型微型计算机系统,2016,37(3):505-509.
[9]陈红玉,孟彩霞.基于相干函数无偏估计的数据恢复技术[J].科技通报,2016,32(3):105-108.
[10]陈亦平,陈伟彪,姚伟,等.WAMS错误数据的快速辨识及恢复方法[J].电力自动化设备,2016,36(12):95-101.
[2]周虹,陈锋.一种云计算共享数据完整性公开审计方案[J].电子设计工程,2016,24(9):60-62.
[3]崔立鲁,朱贵发.利用重力卫星数据恢复地球质量迁移方法的研究[J].科学技术与工程,2015,15(14):106-109.
[4]向劲松,王举,吴涛,等.基于脉冲展宽波形的光脉冲位置调制异步采样信号的数据恢复技术[J].光学学报,2017(1):74-81.
[5]韩利华,程聪.遮挡物体的图像恢复方法研究与仿真[J].计算机仿真,2016,33(11):345-348.
[6]刘金明,谢秋菊,王雪,等.基于GSA-SVM的畜禽舍废气监测缺失数据恢复方法[J].东北农业大学学报,2015,46(5):95-101.
[7]杨立东,王晶,谢湘,等.基于低秩张量补全的多声道音频信号恢复方法[J].电子与信息学报,2016,38(2):394-399.
[8]白晋国,孙红胜,胡泽明.一种基于SQLite3文件格式的删除数据恢复方法[J].小型微型计算机系统,2016,37(3):505-509.
[9]陈红玉,孟彩霞.基于相干函数无偏估计的数据恢复技术[J].科技通报,2016,32(3):105-108.
[10]陈亦平,陈伟彪,姚伟,等.WAMS错误数据的快速辨识及恢复方法[J].电力自动化设备,2016,36(12):95-101.