Research Of Data Transmission Strategy Based On Network Coding In Vehicular Ad Hoc Network

With the maturity of Vehicular Ad Hoc Network (VANET), a large number of applications are extended gradually, such as transportation safety, resource sharing and media entertainment download. However, VANET is different from traditional wireless Mesh ad hoc network. With topology changing dynamically, VANET is intermittent connection, resulting in unstably connection among vehicles. According to the vehicle nodes density, VANET can be divided into dense region and sparse region. In dense region, the speed of vehicle nodes is similar, and the probability of meeting is large, therefore vehicle can make connection with other vehicles, then forwards the data immediately. But the vehicle nodes density in sparse region are too small to forward the data with vehicle immediately. The opportunity to meet is limited, so compared to dense region, the transmission performance is worse in sparse region.Network coding permits vehicle nodes to process data packets before sending them out, significantly reduces the number of packets sent, which improves the throughput. According to the different scenarios, this thesis designs two transmission strategies based on network coding. The main purpose is to further improve the transmission performance in dense region, and ensure that data also can be transmitted reliably in sparse region.The main researches of this thesis are:(1) In dense region, this thesis proposes a transmission strategy based on network coding with multi-generation mixing, we call it ORLNC. About this strategy, it first optimizes the traditional random linear network coding in each generation, and designs the network coding with inter-generation (INC). In this INC, each generation is not independent but related, that means one generation of encoded packets includes all previous generations that have been encoded. In the case of packet loss, the purpose vehicle node can recover the lost previous generation encoded packet with later generations, and decode them timely. Then focus on next forwarding vehicle node, according to the vehicles’motion state, this thesis designs the method of selection metrics based on minimum path approximation degree, and each vehicle node updates this value regularly. The vehicle node, which own the largest value of minimum path approximation degree, is used as the next forwarding node. The experimental results show that ORLNC can effectively improve the transmission rate of data packets and the throughput of VANET.(2) In sparse region, on the basis of multi-generation network coding, this thesis proposes a transmission strategy (RORLNC) based on RSU. RSU restores and transmits the data packets indirectly, which delivered from vehicles. RORLNC also applies multi-generation network coding in source vehicle node. What is more, according to the number of meeting, this thesis designs the vehicle nodes metric based on suitability values, and according to the number of encoded packets in RSU and repeat numbers, this thesis designs the packets metric based on priority. Besides, RORLNC permits RSU to update the suitability value of each vehicle and the priority of encoded packets regularly, and chooses the highest priority encoded packet to forward to the vehicle, whose suitability value is the biggest. The experimental results show that RORLNC also ensure the data to be transmitted reliably in sparse region.