Distributed crowd filtering mechanism based on heterogeneous network delay and data packet loss constraint

Abstract

The differences among heterogeneous networks, network delay, and data packet error could decline network performance. In order to solve the above problems, we study a kind of distributed crowd-filtering mechanism. This mechanism can effectively control the heterogeneous network diversity delay by updating the coordination signal matrix, the aggregation signal matrix, and the control signal matrix. The mechanism can effectively improve network reliability based on the packet loss constraint. Considering the influence of heterogeneous network latency on the reliability of data mining results, we studied the crowd-filtering scheme for eliminating the effect of packet loss on the efficiency of data filtering. Experimental results show that, compared with the ant colony algorithm, the distributed crowd filter can accurately predict the data position, reduce the filtering error, and improve the classification accuracy and the data characteristics.