GDL

Reliability Assessment Model for Big Data Structure of Internet of Things

To improve Big Data reliability, the Big Data Structure of Internet of Things should consider different reliability rules while building the Big Data Structure of Internet of Things. In this paper, an assessment model to assess Big Data Structure of Internet of Things is presented. This assessment model is based on two different reliability rules: connection degree and relevance. The main goal of this research is to implement an early assessment of the Big Data Structure of Internet of Things for the purpose of its improvement in order to make the assessing process more productive. Structure Design is an important problem in Big Data engineering. It makes assessing more productive as it executes the assessing in an initial stage of the Big Data development. This assessment model consists of two phases: Big Data Structure of Internet of Things assessment phase, and module assessment phase. The model is confirmed by using a case study: Environmental video System. In each phase, a logical reasoning system is used to perform the assessment process based on connection degree and relevance assessing rules. The experimental results show that assessment model is efficient and gave a certain improvement to the Big Data reliability process.

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