The ever-increasing demand of storage capacity and system performance leads to the scaling requirement in redundant arrays of independent disks (RAID)-structured storage systems. Existing approaches mainly focus on minimizing data migration in offline scenario, but not consider the user accesses issued by applications. However, in online scenario, the scaling I/Os and user I/Os usually interfere with each other, and result in significant performance degradation. Thus, it is of big significance to develop an efficient online scaling scheme to mitigate the impact of I/O interference. In this paper, we propose popularity-based online scaling (POS), which exploits workload locality by scaling storage zones with high popularity in a higher priority. POS can efficiently alleviate the interference between scaling I/Os and user I/Os, and it is also general enough to scale various RAID systems like RAID-0, RAID-5, and RAID-6. It can also be readily deployed atop various conventional RAID scaling approaches to improve their performance. To demonstrate the effectiveness of POS, we implement various conventional RAID scaling approaches, and also implement POS on top of these approaches for comparison. Extensive simulations with real-world workloads show that POS can efficiently reduce the response time of user requests and scaling I/Os, and also improves the sequentiality of data accesses.

In cloud computing, how to use limited hardware resources to meet the increasing demands has become a major issue. KSM (Kernel Same-page Merging) is a content-based page sharing mechanism used in Linux that merges equal memory pages, thereby significantly reducing memory usage and increasing the density of virtual machines or containers. However, KSM introduces a large overhead in CPU and memory bandwidth usage due to the use of red-black trees and content-based page comparison. To reduce the deduplication overhead, in this paper, we propose a new design called AMT-KSM, which leverages array mapped tries to realize lightweight memory deduplication. The basic idea is to divide each memory page into multiple segments and use the concatenated strings of the hash values of segments as indexed keys in the tries. By doing this, we can significantly reduce the time required for searching duplicate pages as well as the number of page comparisons. We conduct experiments to evaluate the performance of our design, and results show that compared with the conventional KSM, AMT-KSM can reduce up to 44.9% CPU usage and 31.6% memory bandwidth usage.

Institute of Automation Chinese Academy of Sciences, 95 Zhongguancun East Road, 100190, Beijing, China

Error correcting code (ECC) is an essential method in protection of NAND Flash memories. Complexity of it is increasing rapidly with the increment of error correction capability. Traditionally, the software implementation of ECC which has less cost and high flexibility is nearly ignored due to its inefficiency. This situation can be changed by design of faster software-based ECC scheme. We have found that the reliability is constantly changing with Program/Erase cycles and retention time during the lifetime of memories. However, regular ECC methods fail to take into account the variable kinds of reliability and result in a great waste of computations. In order to achieve better software implementation, an adaptive ECC scheme is proposed to provide various amount of protection. By assigning appropriate ECC, an adaptive ECC with Hamming and more efficient BCH codes is designed to provide corresponding protection. Proposed ECC scheme is suitable for diverse devices and applications. The coding time can be obviously decreased, making it possible to replace hardware methods with software methods.