DocumentCode
58734
Title
Bio-Inspired Routing Algorithms Survey for Vehicular Ad Hoc Networks
Author
Bitam, Salim ; Mellouk, Abdelhamid ; Zeadally, Sherali
Author_Institution
Dept. of Comput. Sci., Univ. of Biskra, Biskra, Algeria
Volume
17
Issue
2
fYear
2015
fDate
Secondquarter 2015
Firstpage
843
Lastpage
867
Abstract
Vehicular Ad hoc NETworks (VANETs) play a key role in the design and development of Intelligent Transportation Systems (ITS) that aim to improve road safety and transportation productivity. VANETs cover vehicle-to-vehicle and vehicle-to-roadside communications. One of the most important challenges of this type of network is the timely and reliable dissemination of messages among vehicular nodes that enable drivers to take appropriate decisions to improve road safety. In the past decade, many routing protocols for VANETs that can support reliability and safety requirements have been proposed. These protocols suffer from several limitations, including complexity, lack of scalability to large scale networks, routing overheads, etc. To address these limitations, various bio-inspired approaches have been proposed to route packets among vehicular nodes in an optimized manner. We survey recent proposed bio-inspired routing algorithms for the VANET environment. In particular, we identify the key features, strengths, and weaknesses of these algorithms and compare them by using various criteria. Moreover, we propose a unified formal model of the bio-inspired multimodular approaches applied to VANET routing. We highlight main future research directions in this area.
Keywords
road safety; routing protocols; telecommunication network reliability; vehicular ad hoc networks; ITS; VANETs; bio-inspired multimodular approach; bio-inspired routing algorithms; intelligent transportation systems; reliability; road safety; routing protocols; safety requirements; transportation productivity; vehicle-to-roadside communications; vehicle-to-vehicle communications; vehicular ad hoc networks; vehicular nodes; Routing; Routing protocols; Safety; Standards; Vehicles; Vehicular ad hoc networks; Wireless communication; Bio-inspired Algorithm; Reinforcement Learning; Routing Optimization; Vehicular Ad-hoc Network; Vehicular ad hoc network; bio-inspired algorithm; reinforcement learning; routing optimization;
fLanguage
English
Journal_Title
Communications Surveys & Tutorials, IEEE
Publisher
ieee
ISSN
1553-877X
Type
jour
DOI
10.1109/COMST.2014.2371828
Filename
6967690
Link To Document