The Department of Computer Science at the University of Cyprus cordially invites you to the PhD Defense entitled:
Speed Adaptive Information Dissemination in Vehicular Ad-Hoc Networks
Speaker: Yiannos Mylonas
A significant issue in vehicular ad hoc networks (VANETs) is the design of an effective broadcast scheme which can facilitate the fast and reliable dissemination of emergency warning messages (EWM) in the vicinity of an unexpected event, such as a car accident. In this work we propose a novel solution to this problem, which we refer to as Speed Adaptive Probabilistic Flooding. The scheme employs probabilistic flooding to mitigate the effects of the broadcast storm problem, typical when using blind flooding, and its unique feature is that the rebroadcast probability is regulated adaptively based on the vehicle speed to account for varying traffic densities within the transportation network. The motivation behind this choice is the identification of the existence of phase transition phenomena in probabilistic flooding in VANETs which dictates a critical probability is affected by the varying vehicle traffic density, and shown to be linearly related to the vehicle speed (a locally measurable quantity). The protocol enjoys a number of benefits relative to other approaches: it is simple to implement, it does not introduce additional communication burden, as it relies on local information only, and it does not rely on the existence of a positioning system (e.g. GPS) with its associated high signaling overhead for the exchange of beacon messages for mutual awareness. The scheme is evaluated on different sections of the highway system in the City of Los Angeles and Cyprus, using an integrated platform combining the OPNET Modeler and the VISSIM simulator. Simulation results indicate that the proposed scheme fulfills its design objectives, as it achieves high reachability and low latency of message delivery in a number of scenarios. The scheme is shown to be independent of the number of lanes of the freeway where it is applied, and it continuous to perform as required when uni-directional traffic is replaced by bi-directional traffic. Moreover, the SAPF algorithm has been shown to outperform blind flooding in all scenarios and especially in cases of heavy congestion. Its robustness with respect to different number of hops, different speed limits on the freeway where it is applied, and different transmission range of the vehicles participating in the VANET has also been demonstrated. Finally, the performance of the SAPF algorithm is shown to be comparable to schemes which offer increased opportunities to exhibit superior performance by assuming the presence of GPS systems on board the vehicles.
Yiannos received his B.Sc in Computer Engineering from Oregon State University in 1998. In 2001, he received his M.Sc in Computer Science from University of Cyprus. He is currently pursuing his PhD degree at the University of Cyprus under the supervision of Prof. Andreas Pitsillides. From 1998 until 1999 he worked for Intel Corporation as a product support engineer. Since 2001, he is working as a Special Teaching Staff in the department of Computer Science at the University of Cyprus. His research interests include, Computer Networks, Vehicular Ad-Hoc Networks and Intelligent Transportation Systems (ITS).
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