The Design Of Routing Algorithm Based On Swarm Intelligence In Mobile Social Networks

Mobile social network(MSN) is a type of delay-tolerant networks considering social characteristics of the terminal nodes. Existing DTN routing protocols, assume that there is at least one complete communication path between the source and the destination node, which means that they cannot be applied to MSN directly. Under the circumstance of inexistence of a complete path between the source and the target node, the key to solve the problem of content distribution is how to transmit the data to the target user. At present, although some routing algorithms for DTN can be applied to some extent, they do not consider the social characteristics of the nodes in the network, as a result, the transmission efficiency is relatively low. In recent years,Some scholars have tried to introduce social characteristics of the node when designing algorithms to improve routing efficiency. However, they hardly considered the selfish nodes. These facts have limited the application of mobile social networks. In this paper, we present MSN algorithms based on swarm intelligence, utilizing the theories of ant colony optimization, particle swarm optimization, etc.Firstly, we summarize the general model of mobile social networks. On this basis, we make full use of social characteristics of nodes and propose a mobile social network routing algorithm based on ant colony optimization. In order to get the list of information between the nodes, the algorithm uses the method of processing nodes on the path of information transmission, which provides information for other nodes when they are choosing the next hop. However, the ant colony algorithm is easy to fall into local optimum,we try to combine PSO with ant colony algorithm so that the ants will also have characteristics of particles. Finally, based on selfish nodes in the network, we propose incentives based on the reputation of values. We consider the degree of node’s willingness and the evaluation of other nodes. The only way to get the other node’s service is to participate in the cooperation. By applying this kind of mechanism, users are encouraged to increase the probability of data forwarding, which solved the node selfishness problem to a certain extent.The simulation experiment on real data sets shows that comparing with typical DTN routing algorithms, our algorithm can effectively improve the critical performance of data distribution at small cost of the traffic control. What’s more, the proposed routing algorithm and incentive mechanism can improve the efficiency of the data transmission and suppress the nodes’ selfish behavior. The above work optimized the MSN environment and improved the experience of the mobile users, providing great prospect for the further development of the MSN.