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A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks (MDDV). Evgueni (Eugene) Khokhlov. A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks. Hao Wu Ph.D. Richard Fujimoto Ph.D. Randall Guensler Ph.D. Civil Engineering (transportation department)
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A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks (MDDV) Evgueni (Eugene) Khokhlov Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks • Hao Wu Ph.D. • Richard Fujimoto Ph.D. • Randall Guensler Ph.D. Civil Engineering (transportation department) • Michael Hunter Ph.D. • At Georgia Institute of Technology Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks • Purpose: • I.T. (mobile & wireless communications) in Surface transportation Systems • Enhance communication in existing intelligent transportation systems. • “The Intelligent Transportation Systems (ITS) program is a worldwide initiative to add I.T. to transport infrastructure and vehicles. • Also known as part of Telematics in Europe “the science of sending, receiving and storing information via telecommunication devices.“ Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks • Current ITS (Intelligent Transportation Sys) • Infrastructure heavy • Rely on roadside sensors, cameras, networking === > $$$ • Hard for gov. agencies to get $$$ for ITS Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks • Trend: • Equip cars with computing and communication capabilities thus: • Reduce dependency on the government • As cars are replaced so as the equipment • How to avoid traffic Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks • MDDV is designed to exploit vehicle mobility for data dissemination: • MDDV combines: • Opportunistic forwarding • Trajectory based forwarding • Geographical forwarding Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks V2V network (vehicle to vehicle ad-hoc) contains GPS, digital map, and sensors. • Predictable (high mobility) • Dynamic (rapidly changing topology) • Constrained (one dimension movement) • Potentially large scale • No power constraints Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks V2V network: • Trees are undesirable, • Localized algorithms based on vehicles interacting with neighbors are preferred. Problems: • Unreliable communication channels • Vehicle failure • High mobility Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Data dissemination – transport of information to intended receivers (“all vehicles going to UIC”, “police cars that are close by”). • Low delay • High reliability • Low memory occupancy • Low message passing overhead. Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Data Delivery Mechanism: Opportunistic forwarding: targets networks when an end-to-end path cannot be assumed to exist. Messages are stored and forwarded to another node, a copy may remain with the original and be forwarded again later to improve reliability Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Data Delivery Mechanism: Trajectory based forwarding: directs messages along predefined trajectories. Messages are moving along the road graph. Helps limit data propagation along specific path and reduces message overhead. Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Data Delivery Mechanism: Geographical forwarding: attempts to move the message geographically closer to the destination. In V2V geographical distance has to be defined as graph distance. Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Assumptions: The vehicle knows the road topology through a digital map and its own location in the road network via a GPS device. Source ID, source loc, generation time, destination region, expiration time, etc, are placed in the message header. Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Deliver a message to all vehicles in/entering region r before time t while the data source s is outside of r Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Propagation depends on vehicle traffic. High vehicle density = fast information propagation Only use vehicles that travel in the same direction as where the message needs to go. Ignore vehicles traveling in the opposite direction. Use smallest sum of weights from the source to the destination region in the weighted road graph. Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Data Exchange: With a peer-based scheme a node talks to encountered peers. Structure-base schemes (clusters, trees) won’t work for this context. Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Two possible data exchange sequences. Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Conclusion • MDDV is designed to address the data dissemination problem in a partitioned and highly mobile vehicular network. Messages are forwarded along a predefined trajectory geographically. Intermediate vehicles must buffer and forward messages opportunistically. Evgueni (Eugene) Khokhlov
A Mobility-Centric Data Dissemination Algorithm for Vehicular Networks Questions? Evgueni (Eugene) Khokhlov