An Effective Transmission Strategy Exploiting Node Preference and Social Relations in Opportunistic Social Networks

With the development of network technology and the advent of 5G communication era, high-frequency radio waves with high bandwidth will become the main choice of signal sources. While promoting the development of a high-speed communication network, a high-frequency radio wave has the problem of limited coverage, which makes opportunistic social network become the mainstream communication method. Since the transmission of a large amount of data in a short time will cause the problem of data redundancy, opportunistic social networks suggest that the most appropriate next hop should be selected to achieve efficient data transmission. At present, there are several routing algorithms based on social relations, which attempt to select the most suitable next-hop node among neighbor nodes by making use of relevant context information and historical interaction between nodes. However, existing data transmission methods in opportunistic social networks mainly focus on the influence of a few social attributes on the similarity between nodes but ignore the transmission preference caused by individual characteristics of nodes. To improve the transmission efficiency, this paper establishes an effective data transmission strategy (ENPSR) exploiting node preference and social relations in opportunistic social networks. In our scheme, individual transmission preferences are obtained by measuring the social attributes and historical information of nodes in the transmission process. The appropriate message delivery decision is determined by the prediction scheme, and the continuous and stable data transmission are realized through the recommendation mechanism. According to the simulation experiments, the average delivery ratio of ENPSR algorithm is 0.85, which is 20% higher than that of the epidemic algorithm.