Distance prediction and multi-criteria decision based layering routing for underwater acoustic networks
Underwater sensor nodes may move with the water current,resulting in a highly dynamic network topology,which brings about challenges for the routing in underwater acoustic network(UAN).To cope with the challenges of node mobility and energy efficiency in UAN,this paper proposed a distance prediction and multi-criteria decision based layering routing for underwater acoustic networks(DMD-LR).To predict the distance between nodes,this paper presented a gray Markov inter-node distance prediction model based on an improved gray prediction model.According to the prediction results based on the gray Markov distance prediction model,it provided an effective neighbor node determination rule.Further,it proposed a grey re-lational analysis model based on multi-criteria decision to calculate the grey relational degree(GRD)of neighbor nodes,and selected the neighbor node with the highest GRD as the optimal next hop.It conducted extensive experiments with the NS3 net-work simulation simulator to evaluate the performance of the DMD-LR protocol.The results show that the DMD-LR protocol has great advantages in improving packet delivery rate,reducing end-to-end delay,and lowering total energy consumption compared with the LEER,DBR,VBF,LR-NMP,and IATLR protocols.
万方数据
维普
