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MAP BASED ROUTING IN LARGE SCALE URBAN VEHICLE NETWORKS

MAP BASED ROUTING IN LARGE SCALE URBAN VEHICLE NETWORKS

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MAP BASED ROUTING IN LARGE SCALE URBAN VEHICLE NETWORKS

AGENDA

Exploratory Research• Stable vs.

unstable• Transmission

collision

Optimal Algorithm• Two Variants• Inefficiency of

existing algorithms revealed

• Properties of Optimal Routing Path

Map Based Routing• Rationale• Implementation• Simulation

OPTIMAL ROUTING ALGORITHM

Minimum Delay Algorithm (MDA) Minimum Delay and Hops Algorithm (MDHA) Vehicular to Vehicular, Vehicular to Location, Location to

Location

INEFFICIENCY OF EXISTING ALGORITHMS REVEALED Geo routing family:

Performance degrades quickly as transmission distance increases Local maximum is extremely hard to detect

Mobility based routing family Is the behavior of individual node really RELAIBALY predictable? Choice of the length of time frame used in statistical pattern mining Let’s consider the JOINT probability

AN EXAMPLE

PROPERTIES OF OPTIMAL ROUTING PATH Relative spatial stability Relative temporal stability Routing sequence is very dynamic

MAP BASED ROUTING

Switch the respective

Dynamic network with vehicles being nodes

Static structure network with dynamic link weights

Item From To

node vehicles intersections

link contacts roads

Weighted by

Signal quality

Average packet travel time

MODEL FOR A ROAD SECTION

Modeled as a bi-directed link The weight of a link reflects the average packet travel

time over that link𝑃𝑎𝑐𝑘𝑒𝑡 𝑇𝑟𝑎𝑣𝑒𝑙 𝑇𝑖𝑚𝑒= Ϝቆσ𝑉𝑖𝑁 , 𝑁𝐿𝑟𝑜𝑎𝑑 ,𝐿𝑟𝑜𝑎𝑑 ,𝐷𝑣𝑒ℎ𝑖𝑐𝑙𝑒𝑠ቇ+ ℇ

where 𝐿𝑟𝑜𝑎𝑑 ≡ 𝑙𝑒𝑛𝑔𝑡ℎ 𝑜𝑓 𝑡ℎ𝑒 𝑟𝑜𝑎𝑑 𝑠𝑒𝑐𝑡𝑖𝑜𝑛 σ𝑉𝑖𝑁 ≡ 𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑣𝑒ℎ𝑖𝑐𝑙𝑒 𝑠𝑝𝑒𝑒𝑑

𝑁𝐿𝑟𝑜𝑎𝑑 ≡ 𝑙𝑖𝑛𝑒 𝑑𝑒𝑛𝑠𝑖𝑡𝑦 𝑜𝑓 𝑣𝑒ℎ𝑖𝑐𝑙𝑒𝑠 𝑜𝑛 𝑡ℎ𝑒 𝑟𝑜𝑎𝑑 𝑠𝑒𝑐𝑡𝑖𝑜𝑛

𝐷𝑣𝑒ℎ𝑖𝑐𝑙𝑒𝑠 ≡ 𝑡ℎ𝑒 𝑑𝑖𝑟𝑒𝑐𝑡𝑖𝑜𝑛 𝑜𝑓 𝑡ℎ𝑒 𝑣𝑒ℎ𝑖𝑐𝑙𝑒𝑠 The bandwidth of the road section 𝐵𝑟𝑜𝑎𝑑 : 𝐵𝑟𝑜𝑎𝑑 = 𝐸 ۃ

1𝑃𝑇𝑇 ۄ

ALGORITHM ENHANCEMENT

PERFORMANCE

Comm radius 100m, transmission distance 6KM

FACTOR- COMM RANGE

FACTOR- COMM RANGE