Vehicular Networks

CS 795/895

Dr. Michele Weigle
mweigle at cs.odu.edu
 
 
Spring 2008
TR 9:30-10:45 am
E&CS 2120

Research Project

CS 795/895 | Requirements Milestones Groups Topics | Blackboard Submitting Assignments

Requirements

Milestones


Project Proposal

You must get approval on your project topic before submitting your proposal.

Your project proposal should include the following:


Background Presentation


Progress Reports


Final Presentation


Final Paper


Groups

MembersTopicReading List
Samy and Souhail Sensitivity and Reliability in NOTICE
  • Mahmoud Abuelela, Stephan Olariu, and Michele C. Weigle, NOTICE: Architecture for the Notification of Traffic Incidents, Proceedings of the IEEE Vehicular Technology Conference (VTC) - Spring, May 2008. (submitted version, not final).
  • Karpiriski, M. Senart, A. Cahill, V., Sensor networks for smart roads, Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops, 2006. March 2006, pp.-5-.
  • J.-P. Hubaux, S. Capkun, and J. Luo, The security and privacy of smart vehicles, IEEE Security and Privacy Magazine, 2(3), 4955, 2004.
  • Vijetha and Srikanth Location-Based/Location-Aware Services
  • M. Caiskan, D. Graupner, and M. Mauve, Decentralized Discovery of Free Parking Places, Proceedings of ACM VANET, pp. 30-39, 2006.
  • M. Dikaiakos, A. Florides, T. Nadeem and L. Iftode, Location-aware Services over Vehicular Ad-Hoc Networks using Car-to-Car Communication, IEEE Journal on Selected Areas in Communications, 25(8), Oct 2007.
  • Hadi and Brian Congestion Inferencing in NOTICE
  • Mahmoud Abuelela, Stephan Olariu, and Michele C. Weigle, NOTICE: An Architecture for the Notification of Traffic Incidents, Proceedings of the IEEE Vehicular Technology Conference (VTC) - Spring, May 2008.
  • JiST/SWANS. http://jist.ece.cornell.edu, 2004.
  • Emily Parkany and Chi Xie, A Complete Review of Incident Detection Algorithms and Their Deployment: What Works and What Doesn't, New England Transportation Consortium Report NETCR37, Feb 2005.
  • Danda Cross-Layer Optimization for VANETs
  • M.M. Artimy, W. Robertson, W. J. Philips, Assignment of dynamic transmission range based on estimation of vehicle density, VANET 05 Sept,2005
  • Suthaputchakun and Ganz, Priority Based Inter-Vehicle Communication in Vehicular Ad-Hoc Networks using IEEE 802.11e, VTC Spring, 2007.
  • Nathan Balon and Jinhua Guo, Increasing Broadcast Reliability in Vehicular Ad Hoc Networks, 2006.
  • Mo and TalalTraffic Light Control for Emergency Vehicles (TLC4EV)
  • C. Gorgorin, V. Gradinescu, R. Diaconescu, V. Cristea and L. Iftode, Adaptive Traffic Lights using Car-to-Car Communication, Proceedings of the IEEE Vehicular Technology Conference (VTC) - Spring, April 2007.
  • Q. Huang, R. Miller, Reliable Wireless Traffic Signal Protocols for Smart Intersections, Ford Motor Company.
  • T. G. Magomedov, A. B. Ostrovskiy, Simulation of smart traffic lights, Saint Petersburg 2006.
  • Rajat and SpardhaIDM/MOBIL Validation
  • Sommer, C.; Dietrich, I.; Dressler, F, Realistic Simulation of Network Protocols in VANET Scenarios, 2007 Mobile Networking for Vehicular Environments.
  • Jerome Harri, Marco Fiore, Fethi Filali, Christian Bonnet, Claudio Casetti, Carla-Fabiana Chiasserini, A Realistic Mobility Simulator for Vehicular Ad Hoc Networks, Research Report RR-05-150, October 2005.
  • Khaled Ibrahim and Michele C. Weigle, CASCADE: Cluster-based Accurate Synthetic Compression of Aggregated Data in VANETs, in submission, 2008.
  • MadhukeshEvaluation of Data Dissemination Protocols
  • Palazzi, Ferretti, Roccetti, Pau, and Gerla, How Do You Quickly Choreograph Inter-Vehicular Communications? A Fast Vehicle-to-Vehicle Multi-Hop Broadcast Algorithm, Explained, Proceedings of Workshop on Networking Issues in Multimedia Entertainment, 2007.
  • Wegener Axel, Hellbruck Horst, Fischer Stefan, Schmidt Christiane, Fekete Sandor, AutoCast: An Adaptive Data Dissemination Protocol for Traffic Information Systems, Vehicular Technology Conference,2007.
  • NigelLocation Privacy
  • J. Freudiger, M. Raya, M. Felegyhazi, P. Papadiitratos, and J.-P. Hubaux, Mix-Zones for Location Privacy in Vehicular Networks, Proceedings of the International Workshop on Wireless Networking for Intelligent Transportation Systems (WIN-ITS), Aug 2007.
  • J. Guo, J.P. Baugh, and S. Wang, A Group Signature Based Secure and Privacy-Preserving Vehicular Communication Framework, Proceedings of the IEEE Workshop on Mobile Networking for Vehicular Environments (MOVE), pp. 103-108, May 2007.
  • K. Sampigethaya, Mingyan Li, Leping Huang, and R. Poovendran, AMOEBA: Robust Location Privacy Scheme for VANET, IEEE Journal on Selected Areas in Communications, 25(8):1569-1589, Oct 2007.

  • Suggested Topics

    These are just a few suggestions. Feel free to propose your own topic based on your interests. Those of you who took CS 791 last semester may already have an idea of a topic that you'd like to pursue.

    1. Location Privacy In many vehicular networking applications, especially those concerned with security, vehicles periodically broadcast their GPS coordinates along with a unique identifier (such as an ID or a public key). In these situations, an adversary could listen to messages and track the movements of individual vehicles. This presents a serious problem, because it is not protecting the privacy of drivers. Investigate previous approaches to location privacy and propose a new method for ensuring location privacy while maintaining security.

      Suggested Reading: [FRF+07], [SLH+07]

    2. Congestion Inferencing Heuristics for NOTICE The NOTICE system is based upon sensor belts determining when congestion is occuring using data received from passing vehicles. Investigate current automatic incident detection (AID) algorithms used with current monitoring technology. How can NOTICE improve upon these algorithms? Propose what rules, or heuristics, NOTICE belts should use to determine when to signal to passing vehicles that congestion is occurring or that an incident has likely occurred.

      Suggested Reading:
      Emily Parkany and Chi Xie, A Complete Review of Incident Detection Algorithms and Their Deployment: What Works and What Doesn't, New England Transportation Consortium Report NETCR37, Feb 2005.

    3. Mining VDOT Traffic Data - I The Virginia Dept of Transportation (VDOT) maintains a database, called ADMS Virginia, of information collected by loop detectors in the Hampton Roads area. Develop tools to gather and process information about traffic flow in the Hampton Roads area. The ultimate goal is to provide movement traces for realistic simulations.

      Suggested Reading:
      ADMS Virginia
      ADMS Manual

    4. Mining VDOT Traffic Data - II Develop tools to gather and analyze information about incidents in the Hampton Roads area from ADMS Virginia. What are durations of traffic incidents? How often are lanes closed? What is the impact of the incident on traffic (during rush hours vs. non-rush hours)? The ultimate goal is to provide information for realistically simulating various types of traffic incidents.

      Suggested Reading:
      ADMS Virginia
      ADMS Manual

    5. Location-Based/Location-Aware Services Develop an application that takes advantage of a vehicle's knowledge of its location. Typical examples include resource availability and advertising. Investigate previously-proposed approaches and propose a new application.

      Suggested Reading: [CGM06], [DFN+07]

    6. Validating ODU SWANS Extensions Study the validation that was performed for VanetMobiSim (validated against CORSIM). Perform a similar validation for the new ODU SWANS extensions.

      Suggested Reading: J. Harri, M. Fiore, F. Filali, and C. Bonnet, A Realistic Mobility Simulator for Vehicular Ad Hoc Networks, Technical Report, RR-05-150, 2005. (Last updated March 2007).

    7. Implementing Mobility Models in SWANS Implement the Knope and Nagel-Schreckenberg mobility models for the new ODU SWANS extension.

    8. IDM/MOBIL Validation Add extensions to IDM/MOBIL in SWANS to enable dynamic setting of parameters to allow for the simulation of different types of vehicles/drivers in the same simulation. Also, validate the IDM/MOBIL implementation by comparing it against Treiber's MicroApplet.