Kalman Prediction-Based Neighbor Discovery and Its Effect on Routing Protocol in Vehicular Ad Hoc Networks

Efficient neighbor discovery in vehicular ad hoc networks is crucial to a number of applications such as driving safety and data transmission. The main challenge is the high mobility of vehicles. In this paper, we proposed a new algorithm for quickly discovering neighbor node in such a dynamic envir...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems Vol. 21; no. 1; pp. 159 - 169
Main Authors: Liu, Chunfeng, Zhang, Gang, Guo, Weisi, He, Ran
Format: Journal Article
Language:English
Published: New York IEEE 01-01-2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:Efficient neighbor discovery in vehicular ad hoc networks is crucial to a number of applications such as driving safety and data transmission. The main challenge is the high mobility of vehicles. In this paper, we proposed a new algorithm for quickly discovering neighbor node in such a dynamic environment. The proposed rapid discovery algorithm is based on a novel mobility prediction model using Kalman filter theory, where each vehicular node has a prediction model to predict its own and its neighbors' mobility. This is achieved by considering the nodes' temporal and spatial movement features. The prediction algorithm is reinforced with threshold triggered location broadcast messages, which will update the prediction model parameters, and improve the efficiency of the neighbor discovery algorithm. Through extensive simulations, the accuracy, robustness, and efficiency properties of our proposed algorithm are demonstrated. Compared with other methods of neighbor discovery, which are frequently used in HP-AODV, ARH, and ROMSG, the proposed algorithm needs the least overheads and can reach the lowest neighbor error rate while improving the accuracy rate of neighbor discovery. In general, the comparative analysis of different neighbor discovery methods in routing protocol is obtained, which shows that the proposed solution performs better than HP-AODV, ARH, and ROMSG.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2018.2889923