Research On Trusted Opportunistic Routing Mechanism For Load Balancing In MANET Based On Trust Model

In Mobile Ad Hoc Network(MANET),opportunistic routing can effectively improve network performance.However,opportunistic routing also has security issues.For example,malicious nodes can easily be mixed into the node candidate set,thereby disturbing network performance.Aiming at the problem of malicious nodes in opportunistic routing and forwarding candidates,a trust model based on node behavior is proposed.The trust model uses pruning and filtering mechanisms to remove malicious suggestions,and uses a dynamic weight calculation method when calculating the comprehensive trust value.It combines direct trust and indirect trust to filter and filter low-trust nodes in the network.Then,combining the ETX(Expected Transmission Count)value and the node trust value,a trust model-based opportunistic routing algorithm BTOR(Opportunistic routing algorithm based on trust model)is proposed.A large number of simulation results show that the algorithm can significantly improve network performance and reduce the interference of malicious nodes to the network system.In the network environment,node trust evaluation is accompanied by extra energy consumption.In view of the extra overhead and insufficient energy consumption optimization caused by using trust model in opportunistic routing,this paper proposes a load balancing opportunistic routing algorithm.Considering the trust value of nodes,the expected cost of forwarding and maintenance and the residual energy of nodes,this algorithm proposes an opportunistic routing algorithm tceor(based on trust value,cost and energy,opportunistic routing)based on the trust value,the expected cost of forwarding and maintenance and the residual energy of nodes.According to the algorithm,the optimal next hop node is selected to reduce the network energy consumption and increase the network lifetime.In addition,the optimal forwarding region is determined according to the node density and distance in the network to further balance the load between different next hop candidates.Comparative experiments show that the proposed algorithm can effectively improve the network performance in terms of energy consumption,delay and packet delivery rate.