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A greedy perimeter stateless routing method based on a position prediction mechanism for flying ad hoc networks

Authors :
Mehdi Hosseinzadeh
Jawad Tanveer
Liliana Ionescu-Feleaga
Bogdan-Stefan Ionescu
Mohammad Sadegh Yousefpoor
Efat Yousefpoor
Omed Hassan Ahmed
Amir Masoud Rahmani
Asif Mehmood
Source :
Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 8, Pp 101712- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Today, unmanned aerial vehicles (UAVs) are very popular in military and commercial applications as well as academic research. Flying ad hoc network (FANET) is a new type of ad hoc network that organizes small drones in an ad hoc form. The movement in 3D space, high mobility, frequent topological changes, restricted resources, and low density are the features of these networks. These features cause serious challenges in designing an appropriate routing approach for these networks. In this paper, a greedy perimeter stateless routing method based on a position prediction mechanism called GPSR+ is proposed for FANETs. This scheme employs a position forecast strategy to approximate the future position of UAVs and modifies the propagation period of hello messages based on this strategy to achieve better adaptability to the dynamic network. In addition, GPSR+ chooses a set of candidate UAVs using a new method called the spherical removal technique to decide on the next-hop UAVs in the routing process. Finally, the most stable UAV toward the destination will be chosen from the candidate set to act as the next-hop. The simulation results show that GPSR+ grows the packet delivery ratio in FANET and extends network longevity because it increases path stability and improves energy consumption. However, the delay in GPSR+ is high.

Details

Language :
English
ISSN :
13191578
Volume :
35
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Journal of King Saud University: Computer and Information Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.78f63f2a55744692a9271e49dd1d87a4
Document Type :
article
Full Text :
https://doi.org/10.1016/j.jksuci.2023.101712