【摘要】 针对云存储平台中用户隐私和敏感数据的安全保护问题,在前期提出的基于自主可控机制的安全云存储模型ASOM(All Self-Organization Model)基础上,对MDSS端元数据的管理操作、MDSS和DMS之间的通信过程做进一步优化,针对ASOM模型实际场景引入锁思想实现两个节点一致性的Co-Work算法,完成MDSS和DMS节点之间的协同工作和数据的一致性保持。同时,考虑网络带宽对ASOM中读写效率的影响,引入随机表机制,改变DSS上报的时间结点,以提高ASOM整体读写效率。测试结果表明:执行Co-Work算法后的ASOM模型实现了数据的物理与逻辑隔离,保证用户对元数据的自主控制和管理,而且随着数据尺寸增大读写效率明显提高,在数据达到1 GB时读写效率提高了12%。更多还原

【Abstract】 To guarantee the privacy protecting and sensitive data storage in cloud storage, this paper presents a consistency preserving algorithm, Co-Work, based on the actual scene and lock mechanism which can be implemented in ASOM(All Self-Organization Model). Co-Work algorithm can keep consistency between the metadata server and the storage device through a random map. Experimental results show that the ASOM model implemented Co-Work algorithm can isolate the physical data from logical data, avoid the autonomous users to control and manage the metadata, and increase the data transport efficiency. The read/write efficiency can be increased by 12% when the file size reachs 1 GB.更多还原