The Library
Kalman prediction based neighbor discovery and its effect on routing protocol in vehicular ad hoc networks
Tools
Tools
Tools
Liu, Chunfeng, Zheng, Gan, Guo, Weisi and He, Ran (2020) Kalman prediction based neighbor discovery and its effect on routing protocol in vehicular ad hoc networks. IEEE Transactions on Intelligent Transportation Systems, 21 (1). pp. 159-169. doi:10.1109/TITS.2018.2889923
|
PDF
WRAP-Kalman-prediction-neighbor-discovery-effect-routing-protocol-vehicular-Guo-2018.pdf - Accepted Version - Requires a PDF viewer. Download (709Kb) | Preview |
Official URL: https://doi.org/10.1109/TITS.2018.2889923
Abstract
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 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 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.
| Item Type: | Journal Article | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
||||||||||||||||||
| Divisions: | Faculty of Science > Engineering | ||||||||||||||||||
| Library of Congress Subject Headings (LCSH): | Kalman filtering -- Industrial applications, Mobile communication systems, Algorithms | ||||||||||||||||||
| Journal or Publication Title: | IEEE Transactions on Intelligent Transportation Systems | ||||||||||||||||||
| Publisher: | IEEE | ||||||||||||||||||
| ISSN: | 1524-9050 | ||||||||||||||||||
| Official Date: | January 2020 | ||||||||||||||||||
| Dates: |
|
||||||||||||||||||
| Volume: | 21 | ||||||||||||||||||
| Number: | 1 | ||||||||||||||||||
| Page Range: | pp. 159-169 | ||||||||||||||||||
| DOI: | 10.1109/TITS.2018.2889923 | ||||||||||||||||||
| Status: | Peer Reviewed | ||||||||||||||||||
| Publication Status: | Published | ||||||||||||||||||
| Publisher Statement: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||||||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||||||||||||
| RIOXX Funder/Project Grant: |
|
||||||||||||||||||
| Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
