A Time Efficient Approach for Error Location Detection and Correction in Big Data Cloud Storage

The approach, the burst error acknowledgement relies upon the without scale framework topology and a substantial part of disclosure operations driven in obliged transient or spatial data divides as opposed to a whole big data set. From this time forward the recognisable proof and range method can be essentially stimulated. In addition, the acknowledgement and territory endeavours can be appropriated to cloud stage to totally exploit the algorithm power and big storage. Through the investigation on our cloud computing stage of Cloud data storage, it is shown that our proposed methodology can fundamentally diminish the ideal opportunity for error recognition and correction location in big data sets created by extensive scale sensor system frameworks with adequate error distinguishing precision.