Data And Energy Collaboration Routing Algorithm Based On VANET

Intelligent transportation technology has become one of the hot areas of current research.Vehicular Ad-hoc Networks(VANET),as an important part of Intelligent Transport System(ITS),has been receiving widespread attention from scholars around the world in recent years.RoadSide Unit(RSU)is a key component of the VANET infrastructure,which connects mobile vehicles to other infrastructure.Since the deployment of traditional RSU is directly connected through the grid,in this case expensive labor costs and a high carbon footprint are required.The key issues in VANET are to reduce node energy consumption,reduce data transmission delay and improve network life cycle.This paper addresses the higher carbon footprint cost of RSU nodes in VANET and the routing problem between vehicle nodes.By introducing energy harvesting in the RSU node,the energy harvesting function is to collect energy in nature(such as solar energy,wind energy,etc.),as well as data and energy joint update control schemes.Clustering routing algorithm can improve the lifetime of the network,reduce data routing overhead,network delay,etc.The main contribution and innovations are as follows:Firstly,we study the characteristics of VANET routing algorithm is suitable for VANET of VANET brief technical background,characteristics and typical applications,in turn,understand the research status of classic VANET routing and clustering algorithms.Based on a brief analysis of the advantages and disadvantages of various routing protocols,the existing routing criteria have gradually strengthened the consideration of factors that affect routing performance such as speed,distance,and direction.Clustering routing algorithm can significantly improve the scalability of the network,reduce data routing overhead,network delay,etc.Secondly,A new data and energy collaboration routing algorithm in the VANET,which maximizes the network life cycle through energy cooperation between roadside units and energy transmission between roadside units and downstream vehicles.The roadside units node can harvest energy from the nature and also receive down steam vehicle energy dispatch to maintain the energy needed for data transmission,may transfers a portion of obtained energies by roadside units nodes to the neighboring roadside units nodes through energy cooperation.For this case,with no energy cooperation,we show thateach node should allocate more power to links with more noise and/or more data flow.In addition,when there is energy cooperation,our numerical results indicate that the energy is routed from nodes with lower data loads to nodes with higher data loads.By analysing the data rate,transmission power and energy transmission,we solve the problem of maximum network life cycle in the conservation law of energy and traffic.We consider involving energy constraints and data transmission joint problem,we optimize each roadside units nodes energy management over vehicular outgoing data links and its energy transfers to neighboring roadside units nodes.After that,we consider the joint optimization of energy and data traffic.By determining the necessary conditions for the joint optimization strategy of energy and data routing,we provide an Lagrange Newton iterative algorithm to update the data flow,energy flow and power control,so that the algorithm converge faster to the optimal operation point.Finally,the above algorithms are simulated by MATLAB and NS-3 simulation tools.Simulation results show that when the number of RSU nodes is fixed,the situation with energy collection brings a longer network life cycle than without energy collection.With the increase in the number of vehicles,the network life cycle is constantly increasing and eventually stabilizes.When the number of vehicle nodes is fixed,the network life cycle with energy cooperation is much larger than the network life cycle without energy cooperation.But this situation is not absolute.When the number of RSU is less than a certain value,participating in vehicles without energy cooperation is slightly better than participating in the life cycle of vehicle networks with energy cooperation.