SecNVM: An Efficient and Write-Friendly Metadata Crash Consistency Scheme for Secure NVM

Data security is an indispensable part of non-volatile memory (NVM) systems. However, implementing data security efficiently on NVM is challenging, since we have to guarantee the consistency of user data and the related security metadata. Existing consistency schemes ignore the recoverability of the SGX style integrity tree (SIT) and the access correlation between metadata blocks, thereby generating unnecessary NVM write traffic. In this article, we propose SecNVM, an efficient and write-friendly metadata crash consistency scheme for secure NVM. SecNVM utilizes the observation that for a lazily updated SIT, the lost tree nodes after a crash can be recovered by the corresponding child nodes in NVM. It reduces the SIT persistency overhead through a restrained write-back metadata cache and exploits the SIT inter-layer dependency for recovery. Next, leveraging the strong access correlation between the counter and DMAC, SecNVM improves the efficiency of security metadata access through a novel collaborative counter-DMAC scheme. In addition, it adopts a lightweight address tracker to reduce the cost of address tracking for fast recovery. Experiments show that compared to the state-of-the-art schemes, SecNVM improves the performance and decreases write traffic a lot, and achieves an acceptable recovery time.

Metadata Caching Subsystem for Cloud Storage

Cloud storage is a hot topic in current research. Different from previous work, we emphasize the importance of metadata cache in the study of cloud storage. Because the efficiency of distributed file system has much effect on cloud storage The metadata operation accounts for more than 50% of the total file operation. So the strategy of efficient metadata management is important. There are three parts in this paper. We start with a brief introduction of cloud storage. Then a metadata caching algorithm for cloud storage is proposed. An additional discussion of its performance is also provided. The prototype which incorporates the proposed metadata caching algorithm is realized on Luster to evaluate its performance. Comparing experimental results from this study conclude that the metadata caching subsystem can improve the performance of cloud storage.