Geocast routing in vehicular networks for reduction of CO2 emissions
Alsabaan M.; Naik K.; Abdelkader, Tamer; Khalifa T.; Nayak A.;
Abstract
Pollution and gas emissions are increasing and negatively impacting global warming. Consequently, researchers are looking for solutions that save environment. Greenhouse gas (GHG) emissions from vehicles are considered to be one of the main contributing sources. Carbon dioxide (CO 2) is the largest component of GHG emissions. Vehicular networks offer promising technology that can be applied for reduction of CO 2 emissions. One of the major applications of vehicular networks is Intelligent Transportation Systems (ITS). To exchange and distribute messages, geocast routing protocols have been proposed for ITS applications. Almost all of these protocols evaluate network-centric performance measures, instead of evaluating the impact of the protocol on the vehicular system. Nowadays, the harmful effects of air pollutants have been the subject of considerable public debate. Vehicles' stop-and-go condition, high speed, and high accelerations are environmentally unfriendly actions (EUF) that increase the amount of emissions. These actions can happen frequently for vehicles approaching a traffic light signal (TLS). Therefore, we propose a new protocol named environmentally friendly geocast (EFG), which focuses on minimizing CO 2 emissions from vehicles approaching a TLS by avoiding the EUF actions. Simulation results demonstrate that the proposed protocol can achieve effective reduction of vehicle CO 2 emissions. © 2011 Springer-Verlag.
Other data
| Title | Geocast routing in vehicular networks for reduction of CO<inf>2</inf> emissions | Authors | Alsabaan M. ; Naik K. ; Abdelkader, Tamer ; Khalifa T. ; Nayak A. | Issue Date | 20-Sep-2011 | Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | ISBN | 9783642234460 | DOI | https://api.elsevier.com/content/abstract/scopus_id/80052793929 26 6868 LNCS 10.1007/978-3-642-23447-7_4 |
Scopus ID | 2-s2.0-80052793929 |
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