W-GPCR Routing Method for Vehicular Ad Hoc Networks
College of Traffic Engineering, Hunan University of Technology, Zhuzhou 412007, China
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Division of Information and Communication Engineering, Kitami Institute of Technology, Hokkaido 090-8507, Japan
Author to whom correspondence should be addressed.
Sensors 2020, 20(12), 3406; https://doi.org/10.3390/s20123406
Received: 25 May 2020 / Revised: 10 June 2020 / Accepted: 13 June 2020 / Published: 16 June 2020
(This article belongs to the Special Issue Convergence of Intelligent Sensing, Networking, and Computing Technologies for ITS)
The high-speed dynamics of nodes and rapid change of network topology in vehicular ad hoc networks (VANETs) pose significant challenges for the design of routing protocols. Because of the unpredictability of VANETs, selecting the appropriate next-hop relay node, which is related to the performance of the routing protocol, is a difficult task. As an effective solution for VANETs, geographic routing has received extensive attention in recent years. The Greedy Perimeter Coordinator Routing (GPCR) protocol is a widely adopted position-based routing protocol. In this paper, to improve the performance in sparse networks, the local optimum, and the routing loop in the GPCR protocol, the Weighted-GPCR (W-GPCR) protocol is proposed. Firstly, the relationship between vehicle node routing and other parameters, such as the Euclidean distance between node pairs, driving direction, and density, is analyzed. Secondly, the composite parameter weighted model is established and the calculation method is designed for the existing routing problems; the weighted parameter ratio is selected adaptively in different scenarios, so as to obtain the optimal next-hop relay node. In order to verify the performance of the W-GPCR method, the proposed method is compared with existing methods, such as the traditional Geographic Perimeter Stateless Routing (GPSR) protocol and GPCR. Results show that this method is superior in terms of the package delivery ratio, end-to-end delay, and average hop count.