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Ultimate Codes: Near-Optimal Mds Array Codes For Raid-6, Zhijie Huang, Hong Jiang, Chong Wang, Ke Zhou, Yuhong Zhao
Ultimate Codes: Near-Optimal Mds Array Codes For Raid-6, Zhijie Huang, Hong Jiang, Chong Wang, Ke Zhou, Yuhong Zhao
CSE Technical Reports
As modern storage systems have grown in size and complexity, RAID-6 is poised to replace RAID-5 as the dominant form of RAID architectures due to its ability to protect against double disk failures. Many excellent erasure codes specially designed for RAID-6 have emerged in recent years. However, all of them have limitations. In this paper, we present a class of near perfect erasure codes for RAID-6, called the Ultimate codes. These codes encode, update and decode either optimally or nearly optimally, regardless of what the code length is. This implies that utilizing these codes we can build highly efficient and …
S-Code: Lowest Density Mds Array Codes For Raid-6, Zhijie Huang, Hong Jiang, Ke Zhou, Yuhong Zhao, Chong Wang
S-Code: Lowest Density Mds Array Codes For Raid-6, Zhijie Huang, Hong Jiang, Ke Zhou, Yuhong Zhao, Chong Wang
CSE Technical Reports
RAID, a storage architecture designed to exploit I/O parallelism and provide data reliability, has been deployed widely in computing systems as a storage building block. In large scale storage systems, in particular, RAID-6 is gradually replacing RAID-5 as the dominant form of disk arrays due to its capability of tolerating concurrent failures of any two disks. MDS (maximum distance separable) array codes are the most popular erasure codes that can be used for implementing RAID-6, since they enable optimal storage efficiency and efficient encoding and decoding algorithms. In this paper, we propose a new class of MDS array codes called …
Providing Flexible File-Level Data Filtering For Big Data Analytics, Lei Xu, Ziling Huang, Hong Jiang, Lei Tian, David Swanson
Providing Flexible File-Level Data Filtering For Big Data Analytics, Lei Xu, Ziling Huang, Hong Jiang, Lei Tian, David Swanson
CSE Technical Reports
The enormous amount of big data datasets impose the needs for effective data filtering technique to accelerate the analytics process. We propose a Versatile Searchable File System, VSFS, which provides a transparent, flexible and near real-time file-level data filtering service by searching files directly through the file system. Therefore, big data analytics applications can transparently utilize this filtering service without application modifications. A versatile index scheme is designed to adapt to the exploratory and ad-hoc nature of the big data analytics activities. Moreover, VSFS uses a RAM-based distributed architecture to perform file indexing. The evaluations driven by three real-world analytics …