Routing Algorithm Based on Trajectory Prediction in Opportunistic Networks

Abstract

Due to the dynamic change of the opportunistic network topology and the lack of stable information transmission paths between nodes, the traditional topology-based routing algorithm cannot achieve the desired routing performance. To address of this problem, this paper proposes a routing algorithm based on trajectory prediction (RATP). The routing protocol based on trajectory prediction can efficiently and quickly adapt to the network link quality instability and the dynamic changes of network topology. RATP algorithm constructs a node mobility model by analyzing the historical mobility characteristics of the nodes. According to the node prediction information, the metric value of the candidate node is calculated, and the node with the smaller metric value is selected as the data forwarding node, which can effectively reduce the packet loss rate and avoids excessive consumption. Simulation results show that compared with other algorithms, the proposed algorithm has higher data delivery ratio, and end-to-end data delay and routing overhead are significantly reduced.

An Energy-Efficient Opportunistic Routing Protocol Based on Trajectory Prediction for FANETs

“…In the process of trajectory prediction in section IV, in order to obtain more stable movement data of nodes, we set the value of the movement state factor λ to 0.75 [46]. Then, we run the position prediction algorithm at three levels of speed respectively, and the error values obtained are shown in the FIGURE 5.…”

A Novel Routing Scheme for Creating Opportunistic Context-Virtual Networks in IoT Scenarios

“…The authors of [22] presented a classification and a taxonomy of neighbor discovery protocols on IoT scenarios, whose the main goal was to exploit their knowledge about mobility patterns to improve the efficiency in the discovery process. Finally, in [23], the authors proposed a routing algorithm based on trajectory prediction for identifying a mobility model by analyzing the historical mobility characteristics of the nodes and selecting the ones with the best metrics, reducing the packet loss rate, and avoiding excessive energy consumption.…”