Context-aware collect data with energy efficient in Cyber–physical cloud systems

Abstract

Cyber–Physical Cloud System is emerging as a promising system that enables a wide range of applications. In many applications, smart grids, sensing operations generate large amount of data. In order to effectively and efficiently collect large amount of data, a Global view of Context-aware Sensing and Collection (GCSC) scheme is proposed for exploiting both local and global of spatial–temporal correlations to perform data collection in cyber–physical cloud system (CPC system). In a GCSC scheme, the size of the representative region varies according to the residual energy of its smart sensor nodes. For areas far from the sink decrease the size of the representative region to keep high accuracy in the collected data, while areas near the Sink increase the size of the representative region to lower energy consumption to ensure efficient energy management. Thus, the accuracy of sensing data and lifetime can be enhanced at same time. Both theoretical analysis and experimental results indicate that the performance of GCSC scheme is better than the performance in previous studies. Compared with previous schemes, GCSC scheme can improve the data accuracy by 7.56%∼23.16% and increase the network lifetime by more than 11%, also increase energy efficiency as much as 12.39%.