Key Technology Research Of Opportunistic Network Based On Relay Node Assisted Communication

Opportunistic network is an intermittent network in which there is no end-to-end connection between source and destination,and communication is achieved through the chance of encounter between nodes,works in “store-carry-forward”.In humandominated opportunistic networks,nodes are social.The existing node sociality-based opportunistic network routing strategy does not consider the impact of the social characteristics of node movement on message transmission,and for this problem,this paper proposes the opportunistic network routing strategy based on relay node collaboration（BRCR）.The number and location of fixed relay node（FR）introduced in routing strategy affects the performance of the routing strategy,and to further improve the routing performance,this paper proposes FR node deployment strategy based on BRCR and genetic algorithm（BBGFD）.The main research is organized as follows.（1）In human-dominated opportunistic networks,the impact of the social characteristics of node movement on message transmission is analyzed.By adding fixed relay nodes and mobile relay nodes with sufficient resources and robustness in the network to assist communication,an opportunistic network routing strategy based on relay node collaboration is proposed.In the strategy,a relatively stable path is established between source and destination,and efficient message transmission is achieved through the collaboration between common nodes and relay nodes.Experimental results show that the routing strategy has a better message transmission efficiency.（2）In order to improve the performance of the BRCR,the FR node deployment strategy based on BRCR and genetic algorithm is proposed for the problem of fixed relay node deployment.In this strategy,the hot-spot areas in the network are encoded into chromosomes,and the network effectiveness is used as the fitness evaluation of individuals.A FR deployment scheme with a smaller number of FR nodes and better performance is finally obtained through genetic algorithm.Experimental results show that the deployment strategy deploys fewer FR nodes in the network,and effectively improves the performance of the BRCR.