RETRACTED ARTICLE: A data layout method suitable for workflow in a cloud computing environment with speech applications

Abstract

A data layout method suitable for workflow in a cloud computing environment with speech applications is designed and implemented in this research. With the continuous advancement of cloud computing, Internet of Things, wireless communications, mobile Internet and other technologies, data is growing and accumulating at an unprecedented rate. This paper provides the novel efficient speech data processing layout considering prior information and the data structure. On the basis of in-depth research on existing data layout strategies, this paper summarizes several aspects such as incompatibility with energy-saving modes based on storage area division, incompatibility with the heterogeneous HDFS clusters, inflexible data block segmentation algorithms, and randomness of general storage node selection aspects. Especially, considering that speech data related lower-case read-ahead and basic read-ahead are quite different, reflected in the purpose of read-ahead, read-ahead objects, read-ahead execution level, read-ahead trigger conditions, read-ahead feasibility, we propose the efficient robust data mining model to capture the data structure and feature. Through comparing with the other state-of-the-art models, the experiment section gives the clear analysis on the performance.