The Research Of Cooperative Transmission Algorithms Based On Community Nodes In Opportunistic Networks

With the rapid growth of network traffic in recent years,opportunistic networks have been considered a cheap but effective solution to relieve the pressure of current and future network traffic growth.But classical opportunistic network algorithms cannot solve problems of the current network,and it has many defects in community node detection and data transmission strategy.Based on the above problems,this research proposes a data transmission model based on dual degree centrality(DDC-DF)and a data cooperative transmission model based on community node(CN-CDTA),which aims to solve the problems of community node detection and data transmission in opportunistic networks.The main contents and conclusions of this research are as follows.(1)A data transmission model based on dual degree centrality(DDCDF)is proposed,which fuses node degree and triangle motif network’s node degree through the Dempster–Shafer evidence theory to obtain the dual degree centrality metric that can effectively measure the importance of nodes at the macro and micro level of the network.In the process of source node movement,the node with high information dissemination ability can be selected as the next hop and the source data can be forwarded to the destination node more efficiently.Using the real data set and ONE simulator,the DDC-DF model is simulated and compared with other algorithms to verify their performances in terms of delivery rate and average routing overhead.(2)A collaborative data transmission model based on a community node(CN-CDTA)is proposed.The classification of community nodes in the network through a motif-based spectral clustering approach.And three conditions that lead to the change of the community during the node movement are proved by the formula derivation.In the case of satisfied the judgment conditions,the model can make the corresponding adjustment for the changes in the network community.Based on the network community,the influence of community nodes is evaluated through the dual degree centrality,and the appropriate community node is selected to undertake part of the data transmission tasks of the source node.The source node only transmits the remaining part of data,which effectively reduces the energy consumption pressure of the source node.Finally,through the Helsinki data set and ONE simulator,the CN-CDTA model and other comparison algorithms are simulated.The simulation results show that the CN-CDTA model has better performance in delivery rate,average routing overhead,and energy consumption compared with other algorithms.In addition,increasing the same cache size on the CNCDTA model has a higher performance marginal benefit,and it can maintain good stability under different mobile model environments.