Research On Message Forward Mechanism Based On Community In Opportunistic Networks

Opportunistic networks as a new mobile ad hoc networks(MANET), evolved from delay tolerant(DTN), mainly consist of a smart phone, PAD, other handheld equipment and a variety of vehicles carrying the mobile communication terminal by the self-organization. Because the opportunistic networks usually does not depend on the infrastructure and there may not exist throughout the end to end connection, instead, rely on mobile nodes and the chance to meet for data forwarding, these characteristics decide the long transmission delay, higher transmission missed rate and lower transmission rate in opportunistic networks. In the traditional networks which are dependent on infrastructure and the resources of the nodes is relatively abundant, however due to limitation of application scenarios, node’s resources, such as processing, storage and energy capacity etc., are relatively limited in the opportunistic networks. So the existing routing protocols based on the wireless networks are not applicable in opportunistic networks. Therefore, to study and solve new forwarding mechanism has become the urgent and one of the hot topics in the current research area in opportunistic networks.In this thesis, first studying the architecture and routing problem of opportunistic networks, and then a new centrality is proposed in opportunistic networks, which is based on the characteristics of the centrality, similarity and community.In the study of centrality in opportunistic networks, focusing on finding a quality metric associated with better relays which are evaluated by Reachable Probability Centrality(RPC) as we proposed. RPC combines the contact matrix and multi-hop forwarding probability based on the weighted social network, thus ensuring an effective relay selection. This paper also proposed a distributed RPC-based routing algorithm, which demonstrates the applicability of our scheme in the decentralized environment of opportunistic networks. Extensive trace-driven simulations show that RPC outperforms other centrality measures and can significantly reduce the data forwarding cost.In the study of community in opportunistic networks, and community can be a good reflection of the network topology. By analyzing the contact rate between nodes to determine whether existing edges in the network in view of the frequent disconnection of nodes in opportunistic networks and the effect of link performance difference on community division. This new community detection algorithm, combining with above mentioned the reachable probability centrality to realize routing forwarding algorithm(C-RPC). The simulation results prove that the proposed routing mechanism than Bubble Rap algorithm in the delivery rate and forwarding efficiency have better performance.The research can apply to the real application in opportunistic networks and provide idea in research on routing protocols in opportunistic networks, so it has good theory value and application prospect.