Balanced Scheduling Method for Big Data of Network Traffic Based on Set-pair Analysis Strategy

Abstract

The continuous surge in the total amount of big data of network traffic leads to excessive data transmission load on the network channel. To effectively alleviate this problem, a scheduling method for regulating big data load is designed and proposed. The link discovery is applied to perform set-pair analysis of network topology awareness; the cloud computing algorithm is used to perform calculations for data transmission; based on the measurement results, traffic routing is controlled and measured to achieve link analysis and reorganization, as well as completing balanced scheduling of traffic big data, which proves that the method can effectively alleviate the big data scheduling load problem and has an important role for research in network optimization fields.