A Cooperative Detection Model Based on Artificial Neural Network for VANET QoS-OLSR Protocol

Amjad El Khatib, Azzam Mourad, Hadi Otrok, Omar Abdel Wahab, Jamal Bentahar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

In this paper, we address the problem of detecting misbehaving vehicles in Vehicular Ad-Hoc Network using VANET QoS-OLSR, Quality of Service-Optimized Link State Routing protocol. VANET QoS-OLSR is a clustering protocol that is able to increase the stability of the network while maintaining the QoS requirements. However, in this protocol, vehicles can misbehave either by under-speeding or over-speeding the road speed limits after clusters are formed. Such misbehavior leads to a widely disconnected network, which raises the need for a detection mechanism. The majority of the existing detection mechanisms are non-cooperative in the sense that they are based on unilateral judgments, which may be untrustworthy. Others employ cooperative detection scheme with evidence-based aggregation techniques such as the Dempster-Shafer (DS) which suffers from the (1) instability when observations come from dependent sources and (2) absence of learning mechanism. To overcome these limitations, we propose a cooperative method using Artificial Neural Network (ANN), which is able to (1) aggregate judgments and prevent the unilateral decisions, and (2) benefit from the previous detection experience by continuous learning. Simulation results show that our model improves the detection probability and reduces the false alarms rate.

Original languageBritish English
Title of host publication2015 IEEE International Conference on Ubiquitous Wireless Broadband, ICUWB 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467365550
DOIs
StatePublished - 10 Nov 2015
EventIEEE International Conference on Ubiquitous Wireless Broadband, ICUWB 2015 - Montreal, Canada
Duration: 4 Oct 20157 Oct 2015

Publication series

Name2015 IEEE International Conference on Ubiquitous Wireless Broadband, ICUWB 2015

Conference

ConferenceIEEE International Conference on Ubiquitous Wireless Broadband, ICUWB 2015
Country/TerritoryCanada
CityMontreal
Period4/10/157/10/15

Keywords

  • Artificial neural networks
  • Neurons
  • Protocols
  • Quality of service
  • Vehicles
  • Vehicular ad hoc networks

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