Mining and Construction of Information Opportunity Cooperation Mode Based on Big Data Fusion Internet of Things

This paper introduces evolutionary game theory as an analysis tool to study the evolution of the cooperative behavior of nodes in the opportunistic network. At the same time, considering the spatial distribution of nodes in the opportunistic network and the corresponding cooperative interaction relationship, the evolutionary graph theory is further applied to study the cooperative behavior in the context of considering the network space. In the collaboration model of this article, the vertices in the evolutionary graph theory are used to represent the nodes in the network, and the edges in the graph represent that the node pairs are within the communication range of each other. The node will play a game with neighboring nodes according to the payout matrix. Through repeated games between nodes, the network reaches a relatively stable final state, and the distribution of nodes with different behaviors in the final state of the network is checked. By adjusting the network parameters, we can analyze the distribution and evolution of cooperation in the network, and study the stability of the network. We realize the credible collaborative evolutionary game model by building a comprehensive simulation platform and verify its effectiveness and scalability. We design and implement an evolutionary game model independent of routing protocols, so that the model can be quickly deployed in traditional routing protocols. Subsequently, simulations verified that the reputation model played a role in guiding nodes to actively participate in network collaboration during the collaborative evolution process. And the greater the strength of the reputation incentive mechanism, the better the effect of the evolutionary model. The evolution model is deployed in multiple routing protocols, verifying that the model can play a role in different routing protocols. In addition, the evolution model can also play a role in different network environments and has good scalability.