Reliability of a Distributed Data Storage System Considering the External Impacts
Gang Kou, Kunxiang Yi, Hui Xiao, Rui Peng
Abstract
With the emergence of the industrial internet of things, distributed data storage systems have become widely used to store the monitoring data of power generation systems. Malicious hackers often try to destroy or steal these confidential data by illegally invading the systems. In addition to hackers’ illegal intrusions, the availability of the data stored is also affected by the internal failures of the system.In this research, two reliability models are formulated to study the reliability of a phased-mission distributed data storage system considering internal failures and illegal intrusion. The first model considers internal failures and data destruction, whereas the second model further considers data theft. Furthermore, the allocation of the data partitions is optimized so that system reliability can be maximized. Numerical experiments demonstrate the effectiveness of the proposed models and algorithms.