An Advanced Emergency Warning Message Scheme based on Vehicles Speed and Traffic Densities
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 5
Abstract
In intelligent transportation systems, broadcasting Warning Messages (WMs) by Vehicular Ad hoc Networks (VANETs) communication is a significant task. Designing efficient dissemination schemes for fast and reliable delivery of WMs is still an open research question. In this paper, we propose a novel messaging scheme, Advanced Speed and Density Warning Message (ASDWM). ASDWM is a broadcast-based scheme that meets design objectives and achieves high saved rebroadcast and reachability, as well as low end-to-end latency of WM delivery. The ASDWM uses vehicle speeds and vehicles density degrees to help emergency vehicles to send WM according to a road condition, adaptively. Simulation results demonstrate the effectiveness and superiority of the ASDWM over its counterparts.
Authors and Affiliations
Mustafa Banikhalaf, Saleh Ali Alomari, Mowafaq Salem Alzboon
Forks impacts and motivations in free and open source projects
Forking is a mechanism of splitting in a community and is typically found in the free and open source software field. As a failure of cooperation in a context of open innovation, forking is a practical and informat...
A Novel Adaptive Grey Verhulst Model for Network Security Situation Prediction
Recently, researchers have shown an increased interest in predicting the situation of incoming security situation for organization’s network. Many prediction models have been produced for this purpose, but many of these...
Optimum Route Selection for Vehicle Navigation
The objective of Optimum Route Selection for Vehicle Navigation System (ORSVNS) article is to develop a system, which provides information about real time alternate routes to the drivers and also helps in selecting the o...
A Portable Natural Language Interface to Arabic Ontologies
With the growing expansion of the semantic web and its applications, providing natural language interfaces (NLI) to end-users becomes essential to querying RDF stores and ontologies, using simple questions expressed in n...
Blood Diseases Detection using Classical Machine Learning Algorithms
Blood analysis is an essential indicator for many diseases; it contains several parameters which are a sign for specific blood diseases. For predicting the disease according to the blood analysis, patterns that lead to i...