Data Dissemination in Vehicular Ad Hoc Networks

1. Data Dissemination in Vehicular Ad Hoc Networks Guohong Cao Department of Computer Science and Engineering The Pennsylvania State University http://www.cse.psu.edu/~gcao

2. Vehicular Ad Hoc Network • VANET has been envisioned to be useful in road safety and many commercial applications • A VANET can be used to alert drivers to potential traffic jams, providing increased convenience and efficiency. • It can also be used to propagate emergency warning to drivers behind a vehicle (or incident) to avoid multi-car collisions • A moving vehicle may want to know the sale information or remaining stocks at a department store or gas station; the available parking lot at a parking place. Vehicle-Vehicle Communication Vehicle-Infrastructure Communication • In this work, we focus on non-safety related data dissemination issues.

3. Data Dissemination in VANET • Push-based data dissemination, where the messages can be efficiently delivered from moving vehicles or fixed stations to other vehicles. • Examples include traffic condition monitoring, road-side e-advertisements, etc. • Pull-based data dissemination/access, where a vehicle is enabled to query information about specific targets. • For example, a vehicle can query the average vehicle speed in a region, the parking lot, hotel availability. • Push-based approach is used for disseminating data that is useful for many people, whereas pull-based approach is used for querying data specific for some user. In practice, a hybrid of push/pull is used

4. Data Dissemination in VANET • Although data dissemination has been studied in database and network area, many unique characteristics of VANET bring out new research challenges. • Due to fast vehicle movement, network topology and channel conditions change rapidly. • The network density is highly dynamic. Different scenarios at day, night, traffic jam. • The vehicle mobility is partially predictable since it is limited by the traffic pattern and the road layout. • Data dissemination techniques should address these unique characteristics

5. Our Techniques • Pull-based approach (IEEE infocom’06) • The predictable vehicle mobility is exploited to get the data quickly • Push-based approach (IEEE TVT’07) • Data are disseminated to several major directions by moving vehicles and then disseminated to other vehicles • Scheduling (ACM VANET’07) • Techniques used in roadside data units to reduce the data access delay

6. Pull-Based Data Access • Task: to deliver a message from mobile vehicle to the fixed site several miles away. • A driver may want to find out the sale information in a store, the room availability in a hotel. • Challenges: • There may be network partitions due to mobility or traffic condition • End-to-end connection through multi-hop is hard to set up. Most existing ad hoc routing protocols such as DSR/AODV may not work well. • Mobility creates opportunities • Buffer and carry the packet when no routes • Forward the packet to the nodes moves into the vicinity which can help packet delivery • Possible to deliver the packet without an end-to-end connection • Different from existing store-carry forward protocols, we make use of the predictable traffic pattern and vehicle mobility to assist data delivery.

7. Vehicle-Assisted Data Delivery (VADD) • Key issue • Select a forwarding path with smallest packet delivery delay • Why not GPSR? • Guidelines • Make the best use of the wireless transmission • Forward the packet via high density area • Use intersection as a opportunity to switch the forwarding direction and optimize the forwarding path Geographically shortest path Fast speed wireless communication

8. VADD Model • Find out the next forwarding direction with probabilistically the shortest delay 1. Estimate the packet forwarding delay (dmn) between two adjacent intersections based on traffic statistics 2. Use the probabilistic method to estimate the expected delivery delay from current intersection to the destination. 3. Generate a linear equation system, and solve it by Gaussian Elimination Output: Priority list of the outgoing directions for the packet forwarding

9. Intersection Forwarding Protocol • Knowing the priority list of outgoing directions, probe the available contact to ensure the packet is forwarded to the preferred directions • Not trivial, need to consider • Location • Mobility • VADD Intersection Protocols • Location First VADD (L-VADD) • Direction First VADD (D-VADD) • Multi-Path D-VADD (M-VADD) • Hybrid VADD (H-VADD)

10. Push-based Data Dissemination in VANET • Task • Deliver the data to all the vehicles within a given area • Applications • Transportation control • E-advertisement • Emergency announcement • Metrics • Dissemination capacity • The maximum number of data items can be disseminated by the system • Delivery ratio • The percentage of the data items can be received by the vehicles • Network traffic

11. Opportunistic Dissemination (OD) • Idea: opportunistic data exchange • Vehicles store and carry the data • Propagate data to the encountered vehicles and obtain new data in exchange • Dissemination capacity is low. Performance suffers when vehicle density is high • Excessive interference • Hard to schedule the transmission • Too many redundant exchanges

12. Crossing Road C-Road Primary Road P-Road Data Pouring Scheme (DP) • Basic idea: explore road layout and partially predictable vehicle moving pattern • Pour the data along several selected Primary Road (P-Road) by periodic broadcasting • All the roads intersected with the P-Roads are called Crossing Roads(C-Roads) • Vehicles on the C-Road passively receive the data when moving through the intersections on the P-Roads. • Techniques to make it reliable • Invalidation • High overhead

13. DP with Intersection Buffering (DP-IB) • Basic idea of DP-IB • Each intersection buffers the data, and rebroadcasts periodically • Data center only broadcasts for data invalidation or refresh the lost data copies. • Objective of DP-IB • Reduce the amount of data poured from the source • Increase the broadcast throughput • Find the broadcast cycle time through analysis

14. Roadside Data Unit Scheduling • Download (query) requests and upload (update) requests to the roadside data unit • Which request to serve at which time is critical to the system performance • Most existing scheduling work does not consider uplink updates

15. Our Contribution • We first propose a basic low complexity scheduling scheme which considers both data size and request deadline • D*S – Deadline* Size, always serve the request with the minimum D*S • Implementation is tricky, to reduce the computation complexity by pruning the search space. • We improve the performance of the basic scheduling algorithm by using broadcasting techniques to serve more requests • D*S/N – Number of pending requests • We study the tradeoffs between service ratio and data quality, and propose a two step scheme to address the tradeoffs between updates and downloads • Data become stale if an upload is missed. • Schedule upload and download with separate queues and different priorities

16. Publications • J. Zhao, Y. Zhang, and G. Cao, "Data Pouring and Buffering on The Road: A New Data Dissemination Paradigm for Vehicular Ad Hoc Networks," IEEE Transactions on Vehicular Technology, to appear • J. Zhao and G. Cao, "VADD: Vehicle-Assisted Data Delivery in Vehicular Ad Hoc Networks," IEEE Transactions on Vehicular Technology(A preliminary version appeared in IEEE INFOCOM’06) • Y. Zhang, J. Zhao, and G. Cao "On Scheduling Vehicle-Roadside Data Access," The Fourth ACM International Workshop on Vehicular Ad Hoc Networks (VANET), 2007 • Papers are available in http://mcn.cse.psu.edu