Research On Adaptive Method Of Neighbor Discovery In IoVs

In the highly dynamic Internet of Vehicles(Io Vs),both the network establishment and routing maintenance require the information of neighbors within one hop of a node,so the accuracy of the neighbor information directly affects the networking efficiency and routing accuracy.Therefore,accurate and fast neighbor discovery is crucial in the Io Vs.In the Io Vs,nodes advertise their presence by exchanging beacon messages and then perceive neighboring vehicles.However,the mobility of the vehicle is generally high,and the rapid movement of the vehicle will cause the communication environment to change rapidly,thereby improving the randomness of the channel.Therefore,in order to combat the high mobility of vehicles and severe channel fading and discover as many neighbors as possible in the Io Vs environment,beacon messages need to be broadcast frequently.Obviously,frequent broadcast will increase communication overhead.In addition,according to the original intention of constructing Io Vs,it includes rich data services,such as high-definition maps and traffic status information.Beacon messages and other data share limited network resources,so the less network resources used for neighbor discovery,the better the network service,which means that a low broadcast frequency of beacon messages is required.However,it can not be guaranteed that all neighbor nodes can be found in time.Therefore,the tradeoff between accuracy and overhead of neighbor discovery is a major problem faced by neighbor discovery in the Io Vs.To address the issues,the influence of mobility,channel randomness and multi-service network on the performance of neighbor discovery is firstly analyzed without considering channel contention,thereby establishing a mobility model and a communication model.Then the neighbor discovery process is analyzed and a mobility-aware adaptive neighbor discovery method(MAAND)is proposed,which can adaptively adjust the broadcast frequency based on mobility and channel randomness.The method can achieve the optimal trade-off between discovery accuracy and cost.Finally,the simulation results show that the proposed method is reasonable and effective.Secondly,from the perspective of actual neighbor discovery,taking into account channel contention,an analysis and application model of network performance for the multi-service scenario of Io Vs is proposed.Then combining the analysis model with the mobility model and channel model,neighbor discovery process in the multi-service network scenario is further analyzed,and a mobility coupling service based adaptive neighbor discovery method(MSAND)is established.This method can give the expression of hit probability of neighbor discovery,which illustrates the quantitative relationship between neighbor discovery performance and vehicle mobility,channel randomness and multi-service network characteristics.Then,under the guidance of theoretical analysis,an optimal neighbor discovery scheme is designed,so that the broadcast frequency can be adaptively adjusted based on mobility,channel randomness and multi-service network characteristics.Optimal trade-off between accuracy and overhead can be realized.Simulation results show that the proposed method has better performance in both cost and accuracy,and can adapt to multiservice network scenarios.