This paper presents a data redundancy method for distributed storage by applying Erasure code to storage system. The method involves some key technologies such as data read and written, failure detection and node redirection, and restoration algorithms. According to the theoretical analysis, this method can efficiently improve the use ratio of storage space as well as enhance reliability and availability for a storage system. Also, it can obtain the same availability of data at the cost of lower redundancy degree compared with many others storage methods. The quantitative analysis of this method’s performance is also given in the paper.
Proc. SPIE. 8920, MIPPR 2013: Parallel Processing of Images and Optimization and Medical Imaging Processing
KEYWORDS: Statistical analysis, Clocks, Digital filtering, Fourier transforms, Data processing, Very large scale integration, Information technology, Convolution, Algorithm development, Computer architecture
This paper presents a hardware-efficient design for the one-dimensional (1-D) discrete Fourier transform (DFT). Once
the 1-D DFT is formulated as the cyclic convolution form, the first-order moments-based structure can be used as the
basic computing unit for the DFT computation, which only contains a control module, a statistical module and an
accumulation module. The whole calculation process only contains shift operations and additions, with no need for
multipliers and large memory. Compared with the traditional DA-based structure for DFT, the proposed design has better
performance in terms of the area-throughput ratio and the power consumption, especially when the length of DFT is
slightly longer. Similar efficient designs can be obtained for other computations, such as the DCT/IDCT, DST/IDST,
digital filter and correlation, by transforming them into the forms of the first-order moments-based cyclic convolution.