Effective Data Transmission Based on Cluster User Communications in Opportunistic Complexity Social Networks

Social networks are very important information dissemination platforms. Messages in social networks are forwarded through encounters formed by moving nodes in opportunistic complexity network. However, with the gradual expansion of the network scale, the amount of data to be transmitted has increased dramatically, which has brought greater load to the entire network. In order to improve this transmission environment, this paper proposes a transmission mechanism that selects cooperative nodes based on the user's interest. In communication, the degree of matching of node preferences is calculated, and highly matched nodes are selected for priority transmission. This method reduces the occupation of cache resources by redundant information in the network by filtering the message transmission mode of the cooperative nodes, and improves the space utilization of the message cache. Through the comparison of experiments and social network algorithms, this method improves the node's cache utilization, reduces the data transmission delay, and improves the overall network efficiency.