Efficient Fault Rules Mining for Multimedia Broadband Services in Power Sensor Network

In order to reduce the fault rate of the broadband multimedia service in the power sensor network and improve the accuracy of network fault diagnosis, an efficient fault association rule mining algorithm is proposed. Aiming at the characteristics of sparse correlation of fault data and large transaction volume, a set intersection strategy based on pruning and cross-counting is designed to realize efficient rule mining and ensure the normal communication of broadband multimedia services on the existing network. In order to verify the effectiveness of the method, a comparative experiment with the original Eclat algorithm is designed. The experimental results show that the improved method has better performance in the face of a variety of data sets with different characteristics.