A Systematic Review of Different Data Compression Technique of Cloud Big Sensing Data

Sensing devices like camera, satellite, earthquake monitoring, video etc., are producing large number of data. Big data techniques paves the way for the handling the more number of data along with streaming data. Cloud computing technology make it easy to store, access and manage the data with low cost. The data compression techniques helps to minimize the data in the cloud and store the data effectively. The aims of the study is to provide a systematic review of the data compression on big sensing processing. The image compression is used to minimize the size effectively and useful for the cloud environment. The deduplication technique is another method is used to compress the data in the cloud and helps in minimize the size. The clustering based compression technique process the cluster for similar data. The three kinds of compression technique in the cloud are investigated in this study. The investigation of this methods shows that the compression technique is still need to be increased in the manner of scalability and flexibility. © 2020, Springer Nature Switzerland AG.