Traffic Data Analysis for Vehicular Network Connectivity Xiaoyan Hong, hxy@cs.ua.edu Associate professor Computer Science The University of Alabama WiMaN Lab http://wiman.cs.ua.edu/mediawiki/index.php/Main_Page DriveSense'14, Norfolk, VA, USA,Oct 30-31, 2014

A trace of exploring realistic traffic data for networking Cellular data group mobility National Household Travel Survey (NHTS) Agenda-Driven Mobility Model UMassDieselNet trace Localized mobility and Virtual Links Time-Varying Contact Graphs for DTN Taxi GPS traces (San Francisco Yellow Cabs) Vehicle mobility and network connectivity Speed up computation Boolean Chain Matrix Multiplication (BCMM) Integrated Road traffic Signal correlation for enhancing communications

National Household Travel Survey (NHTS) People’s movements are driven by their activities Agenda-Driven Mobility Model Generate mobility on the go Use agendas to capture their activities Demographic data Combine social activities and geographical movements Short/long realistic simulations "An agenda based mobility model," 39th ANSS, Huntsville, AL., April, 2006; journal version 2010

UMass DieselNet trace Localized mobility and Virtual Links Time-varying virtual link between two boxes in link delay and loading capacity Capacity-Aware Routing Using Throw-Boxes”, IEEE GlobeCom 2011, Houston, Dec 2011

Time-Varying Contact Graphs “Constructing Time-Varying Contact Graphs for Heterogeneous Delay Tolerant Networks”, IEEE GlobeCom 2012, Dec 2012

Taxi GPS traces Vehicle mobility and network connectivity Hotspots, trip stats, instantaneous velocity profile Connectivity, partitions, delay, reachability Spatial and temporal properties Crowds and clouds 12/1/2018 Analysis of Mobility Patterns for Urban Taxi Cabs”, IEEE ICNC 2012, Hawaii, Jan. 2012

Average Degree of Connectivity 12/1/2018

Motivate alternative taxi haling methods Union Square park, SF Monday, 2-3pm “Taxi Hailing System using Connected Vehicle Technology”, ITS World Congress, 2014

Speed up computation Application: Boolean Chain Matrix Multiplication (BCMM) bitwise manipulation of sparse matrix Efficient storage further scale to parallel processing Application: time varying topological properties, such as multi-hop vehicular connectivity and partitions “Efficient Multihop Connectivity Analysis in Urban Vehicular Networks”, Vehicular Communications, Apr. 2014

Integrated Road traffic Traffic signal correlation for enhancing communications Large scale urban environments Efficiency metrics, vehicle mobility Different signal configurations Correlation Traffic condition Connectivity Xiaoyan Hong, Meng Kuai, etc., under review by a journal, submitted Sept 2014.

What now: Traffic signal correlation Transportation traffic control, mobility, communications Driving behavior and uncertainty More modeling, temporal/spatial varying properties, microscopic features, GIS Large-scale extreme conditions, emergency and recovery, Tuscaloosa, "The Most Livable City in America" in 2011 by the U.S. Conference of Mayors 2011 tornado, recovery/rebuild, for a smart city

Challenges Preprocessing Invalid data records, different formats Selecting for interesting data components Mining for usable subgraphs Use available tools vs develop own Which dataset(s)? Data privacy treatment

Questions? hxy@cs.ua.edu Thank you! Questions? hxy@cs.ua.edu