Research And Implementation Data Transmission Based On Social Network Mechanism In Vanets

In Vehicular Ad Hoc Networks vehicle spontaneously establish the multi- hop wireless network, which form the information sharing platform for traffic network. It can be widely used in modern traffic management, traffic safety prevention, monitoring urban vehicle status, and other fields. In recent years, VANET has become the focus of Ad Hoc Networks research. Data forwarding is the basis of data exchange in VAN ET, and the associated ro uting protocol is critical factors, which affect the performance of network, In Vehicular Ad Hoc Networks, the moving speed of the vehicle node is fast, and the driving of the vehicle is limited by the structure of the streets, the inhomogeneous distribution of the vehicle as well as the traffic rules and so on. The above characteristics of the vehicle cause frequent changing of the network topology and the unstable communication link, which are disadvantageous factors in designing data forwarding. Aimed at the characteristics of vehicle ad-hoc network, This paper research on social network based data transmission mechanism in VANETS. The specific content and contributions include :Firstly proposed data transmission mechanism based on social network in VANETS. Existing research achievement show that the movement of urban vehicle is of obvious social features. Considering generally the topology of social network is higher stability, this paper proposes the multi- hop data forwarding mechanism based on social network in VANET. It can be decreased by a large number of invalid message exchanging between the vehicle and improve the effective utilization of resources in VANET. Meanwhile, this paper use the vehicle moving feature in cities and centrality for depicting the social characteristics of nodes, than design utility calculation method of nodes and distributed message forwarding strategy.Secondly, the research of distributed community detection and centrality calculation method. Encounter probability of nodes in the same community is relatively higher. The node is usually as repeaters for forwarding message. In contrast the typical distributed community detection algorithm, such as k-clique and MODULARITY, in consideration of time and calculation complexity, we found k-clique is suitable for the scene that data forwarding in VANET. Centrality reflects the capacity of meeting different message destination node in the network. Common the measures of centrality in social network have degree centrality and betwee nness centrality, etc. Betweenness centrality cannot be distributed implementation. The number of encounter between vehicles is higher; degree centrality is not easy to measure. So it is not suitable for the mobile vehicle scenarios. According to this feature, this paper proposes mobile entropy to describe the movement regularity of nodes.Thirdly this paper proposes DFDL(Data Forwarding mechanism based on Distributed Learning), DFDL determines the vehicles’ community tags using the encountered time interval and frequency, and calculates the centrality of nodes using the mobile entropy of vehicle movement. In data forwarding, DFDL mechanism selects appropriate relay codes for data packet messages by comprehensively judging the community tags and centrality of nodes.Fourthly The performance simulation of DFDL routing algorithm, using ONE simulation platform, and expanded the function of community detection based on distributed learning and centrality calculation, Helsinki city as the simulation scenario, determine the size of the network, the experimental indexes include with nodes change delivery rate, delivery rate and rate of packets, delivery rate and rate of packets so on, compared DFDL with BubbleRap in performance.