There are many existing routing strategies in complex networks, but there is no uniform standard to measure whether the strategies achieve optimal transmission effect. A pervasive optimized algorithm is proposed. The key factor restricting transmission capacity is maximum betweenness centrality and minimizing it becomes the uniform standard. In order to make betweenness centrality more evenly distributed and balance the traffic load of each node, we use punishment selection method to avoid the nodes with larger betweenness centrality. The simulation results show that the new algorithm could reduce maximum betweenness centrality of existing strategies and improve the network transmittability greatly.
In order to establish a path from source to destination with less routing cost, we propose a directional probabilistic algorithm to broadcast RREQ packets toward the destination. Without any positioning system, the algorithm uses encounter records to predict the direction to destination and sets different forwarding probability for different intermediate nodes. The simulation results show that our algorithm saves 70% routing cost compared to flooding and 20% compared to pure probabilistic algorithm. Furthermore, the new algorithm also shows good performance in other aspects.
This paper proposes an improved AODV protocol with probabilistic forwarding by means of encounter records (ERPP-AODV) in Mobile Ad Hoc Networks (MANETs). With the help of encounter records, the broadcast is mainly restricted in the direction to destination node predicted by searching the node more recently encountered it. The forwarding probability is set dynamically based on the density of the nodes encountered destination. The simulation results show that our proposed protocol reduce the routing overhead and demonstrates good performance in other aspects.
Several broadcast algorithms have been developed in recent years. However, the problem of reducing routing overhead in ad hoc networks is always to be concerned. This paper proposes an improved directional broadcast algorithm based on Brownian motion for AODV protocol (DBB-AODV). We bring Brownian motion into network model and gain the distribution of the nodes which encountered destination before. This algorithm uses encounter records to predict the direction to destination and forwards RREQ packets with reasonable probability according to the distribution just mentioned. Simulation results indicate that DBB-AODV saves up to 20% of average routing overhead compared to the probabilistic protocol and about 80% of the blind flooding.
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