Research On Vertical Handoff Algorithms Based On Hidden Bias Classifier In Vehicle Networking Environment

The rapid rise of current car holdings and the rapid development of Internet and wireless communication technology have brought great convenience to people's travel and communication,but it also brings various problems and challenges,such as traffic congestion,increasing security accidents,and diversification of user needs and so on.The Internet of vehicles,which is made up of heterogeneous vehicular networks,will become an important way to solve these problems.However,due to the relative high-speed movement of vehicle nodes in different types and different coverage networks,switching between networks occurs in this case,and it is easy to produce "ping-pong effect",thus reducing the quality of communication.How to ensure that the vehicle nodes get better communication quality,reduce the number of handover and handover delay in the operation will become the focus of the study.In this paper,the system structure,key technology and advantages of wireless network(VANET,LTE,Wi-Fi)used in the Internet of vehicles are introduced in detail,and the process classification and evaluation index of vertical handover are summarized.The existing vertical handover algorithm is carefully studied.Finally,the algorithms are summarized and analyzed,and the shortcomings and defects of the algorithm are found when the algorithm is applied to the network of vehicles.For the purpose of solve the shortcomings and defects,this paper introduces the Bias classification decision idea.By using the probability of the switching decision,the joint prior probability is obtained,and the joint decision is made using the posterior probability of the network priority.Finally,the simulation environment is built by MATLAB,and the algorithm is compared with the traditional RSS and the vertical handoff algorithm based on the cost function.The results show that the algorithm can basically meet the switching requirements under the environment of the vehicle network,but there are still some problems,such as the inefficiency of the switching effect,the inability to adapt to the adaptive speed change and so on.With the purpose of solve the shortage of Bias classification decision algorithm,this paper introduces the implicit naive Bias classification idea,breaks through the assumption that the original Bias decision is completely independent of the attributes,establishes the relationship between attributes,and introduces the adaptive correction probability,so that the algorithm can be better adapted to the network differences at different speeds.On the one hand,it can effectively reduce the number of switching times and avoid strict rules.The heavy "ping-pong effect",on the other hand,avoids the excessive enhancement of the complexity of the algorithm,so that the algorithm can better adapt to the situation of high speed change under the traffic environment.In order to verify the effectiveness of the improved algorithm,the improved algorithm is simulated in the MATLAB environment,and compared with the original algorithm and other algorithms.The simulation results show that the algorithm can effectively reduce the number of handover,and has a lower algorithm running time,and improves the stability and efficiency of vertical handoff in the environment of the vehicle network.