Multi-Interference Network Optimization Scheduling Model Simulation Analysis of Huge Amounts of Data

There's so much interference in the network information and the use of data nodes have strong randomness, the current data scheduling model is easy to cause conflict data node, results in the decrease of scheduling efficiency, therefore, put forward a new network more interference of huge amounts of data optimization scheduling model, build the network information to be processed characteristic similarity model, the characteristics of the item to be processed to obtain network neighbors, the collaborative filtering algorithm was adopted to realize the network interference filter. Based on the partition for the amount of mass data scheduling tasks is calculated, to obtain huge amounts of data scheduling tasks of subtasks, so as to build huge amounts of data scheduling tasks and data mapping relationships between the nodes. According to the target data transmission in the server's status, the quota of huge amounts of data communication, build huge amounts of data optimization scheduling model. The experimental results show that the proposed model to the scheduling of huge amounts of data, not only high throughput, and transmission rate is fast, has a high operation performance.