Files in this item

FilesDescriptionFormat

application/pdf

application/pdfUILU-ENG-08-2207_DC-236 assembled.pdf (266kB)
(no description provided)PDF

Description

Title:ERP: An Efficient and Reliable Protocol for Emergency Message Dissemination in Vehicular Ad Hoc Networks
Author(s):Hou, I-Hong; Gao, Yan; Tsai, Yu-En; Hou, Jennifer
Subject(s):Vehicular ad hoc networks
Dissemination strategies
Emergency messaging
Power control
Abstract:Many safety-related applications in Vehicular Ad Hoc Networks require fast and reliable emergency message dissemination through multi-hop broadcast. However, the conventional broadcast mechanism is neither efficient nor reliable because it results in serious contention and collisions, which is usually referred to as the broadcast storm problem. In this paper, we propose ERP, a two-phase broadcast protocol that improves both efficiency and reliability. The first phase, a “fast-propagation phase”, is designed to improve efficiency. We explicitly designate forwarders to relay the message and thus ensure both collision free and quick propagation. The second phase, a “loss recovery phase”, enhances reliability. In this phase, nodes overhear the message and repeatedly broadcast it for the benefit of nodes which have not received the message in the first phase. We analytically show that using a density-aware power control mechanism in the second phase can efficiently improve the recovery rate. We also demonstrate how to find the optimal transmission power. Simulation results illustrate that our protocol outperforms probabilistic forwarding, which is currently the most widely studied solution, by a factor of 2 to 3.
Issue Date:2008-05
Publisher:Coordinated Science Laboratory, University of Illinois at Urbana-Champaign
Series/Report:Coordinated Science Laboratory Report no. UILU-ENG-08-2207, DC-236
Genre:Technical Report
Type:Text
Language:English
URI:http://hdl.handle.net/2142/99606
Sponsor:USARO
UT-Battelle
Date Available in IDEALS:2018-04-04


This item appears in the following Collection(s)

Item Statistics