Interconnection Gap for Vehicular Internet Access Presented by Prasun Sinha Authors Zizhan Zheng Prasun Sinha and Santosh Kumar The Ohio State University ID: 1002179
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1. Alpha Coverage: Bounding the Interconnection Gap for Vehicular Internet AccessPresented by: Prasun Sinha Authors: Zizhan Zheng†, Prasun Sinha† and Santosh Kumar*†The Ohio State University, * University of Memphis
2. Internet Access for Mobile VehiclesApplicationsInfotainmentCargo trackingBurglar trackingRoad surface monitoringCurrent ApproachesFull Coverage Wireless Wide-Area Networking (WWAN)Fully Covered WiFi MeshOpportunistic Service Roadside WiFi
3. Current Approach I (of II): Full CoverageWireless Wide-Area Networking3G Cellular Network3GPP LTE (Long Term Evolution)WiMAXEither long range coverage (30 miles) or high data rates (75 Mbps per 20 MHz channel)3 Mbps downlink bandwidth reported in one of the first deployments in US Google WiFi for Mountain View 12 square miles, 400+ APs1 Mbps upload and download rate Not very practical for large scale deployment due to the prohibitive cost of deployment and management3Google Wifi Coverage Maphttp://wifi.google.com/city/mv/apmap.html
4. Current Approach II (of II): Opportunistic Service via In-Situ APsPrototypeDrive-Thru Internet (Infocom’04,05)In-Situ EvaluationDieselNet (Sigcomm’08, Mobicom’08)Interactive WiFi connectivity (Sigcomm’08)Cost-performance trade-offs of three infrastructure enhancement alternatives (Mobicom’08) MobiSteer (Mobisys’07)Handoff optimization for a single mobile user in the context of directional antenna and beam steering Cabernet (Mobicom’08)Fast connection setup (QuickWiFi) and end-to-end throughput improvement (CTP)ProblemsOpportunistic service, no guaranteeUnpredictable interconnection gap4Our solution: an intermittent coverage model that provides predictable data service to mobile users at low costInternetAPAPAP
5. Roadmap Alpha Coverage – An Intermittent Coverage ModelA general definition – intuitive but intractable Two simplificationsAlpha Network Coverage (N -Coverage)Applies when route information is unknown Ex: Burglar trackingAllows a factor log (n) approximationAlpha Path Coverage (P -Coverage) Applies when route information is given Ex: bus trace in DieselNet, cached model in MobisteerAllows a more efficient factor log (n) approximationEvaluationFuture Work
6. Road Network Model and Problem Statement ModelModel a road network R as an undirected graph GR with edge length at most (by inserting artificial intersections if needed). Model a movement as a path on GR (not necessarily ending at intersections). Model access points as points on GR (modeling the worst case of communication range). Given GR and A0 µ V [GR] that models a set of APs previously deployed Determine if the deployment provides the desired coverage (to be defined), and if notFind a minimum set of points A in GR so that when new APs are deployed at these locations, A0 [ A provides the desired coverage.6v5v1v2v3v4v6v7v8 stv9v4v5v1v2v3v6v7v8v9
7. Alpha Coverage: an Intermittent Coverage ModelA deployment provides -Coverage to a road network R if any path of length on GR touches at least one point representing an access-point. FeaturesProvides a guarantee on the worst case inter-contact gapProvides an estimation of the cumulative data serviceChallengesEven verifying -Coverage is NP-complete since there is a reduction from HAMILTONIAN PATH to itSimplified models are needed7
8. Alpha Coverage w/o Route InformationA deployment provides Network Coverage of distance ( N -Coverage for short) if any path f(a,b) with dist(a,b) (graph distance) at least is covered by at least one AP –Coverage implies N –Coverage, but not vice versa 8 stv9v4v5v1v2v3v6v7v8 = 5stv9v4v5v1v2v3v6v7v8-CoverageN -Coverage
9. Alpha Coverage w/o Route Information (Cont.)Polynomial time verifiableThe optimization problem ( N -Cover) is NP-hardReduction from VERTEX COVER restricted to triangle-free, 3-connected, cubic planar graphsO(log |V|) approximationAssumption: New APs are deployed only at the vertices of GR (real or artificial road intersections) Introducing a factor of 2Reduce N -Cover to node version low diameter graph decomposition GVY algorithmHigh computation time complexity for large networks9v1v2v3v4v5v6v7v8v9v1v3v4v6v8 = 2
10. Alpha Coverage with Route InformationMotivation: use route information to design a more efficient algorithmAssumption: a set of paths F is given where |F| = O(p(|V|))Ex 1) a set of shortest paths obtained from a road network databaseEx 2) a set of most frequently traveled paths learned from historical traffic dataDecompose each given path into -pathsA deployment provides Path Coverage of distance ( P -Coverage for short) if any -path in F is covered by at least one AP.Polynomial time verifiable, the optimization problem is still NP-hardO(log |V|) approximation: reduce P -Cover to Minimum Set Cover10
11. Simulation Setting Road networkA 4km x 4km region around the center of Franklin County, OHAbout 1000 intersections, 1300 road segments Obtained from 2007 Tiger/Line Shapefiles + Mercator projectionMoving scenariosRestricted random way point: each movement follows a shortest path and has length at least 5 mobile nodes, moving 1 hour each, 10 scenarios Various speed limits Ns-2 simulationThe transmission range of each AP is 100m11
12. Deployment methodsP –Coverage Rand-1: a set of randomly selected vertices of GRRand-2: a set of points on randomly selected edges of GRRand-3: the region is divided into 50m x 50m cells; APs are deployed at the centers of a set of randomly selected cells.12 An instance of P -Cover, = 3000 mSimulation Setting (Cont.)
13. Simulation Results 1321 APs are usedThe maximum gap for P -Coverage is about 214 sec, bounded by the time spent on two adjacent moves The maximum gap for a random deployment can be larger than 2000 sec Inter-contact gap (sec) = 3000m (m)CDFStandard deviation (sec)
14. Future WorkImprove the efficiency of N-CoverageCombinatorial algorithms for fractional vertex multicut Connected -CoverageConnect each AP to at least one of the gateways with Internet backhaulJoint Coverage and connectivity optimizationA bound on the number of hops to gateways(,)-Coverage: Enabling Assured Data Service Guarantees that each user moving through a path of length has access to at least units of data. Challenges: variable data rates, traffic density, and contact durations; unknown association schedules14
15. Alpha Coverage w/o Route Information (Cont.)Polynomial time verifiable The optimization problem, called N-Cover, is NP-hardThere is a reduction from VERTEX COVER restricted to triangle-free, 3-connected, cubic planar graphsO(log |V|) approximation: reduce N-Cover to Minimum Vertex Multicut Assumption: New APs are deployed only at the vertices of GR (real or artificial road intersections) => introducing a factor 2Step1: Find the set of -pairs, treat their midpoints as terminalsStep2: Solving the fractional vertex multicut problem -- the dual of node version maximum multicommodity flow problemStep 3: Rounding the solution by low diameter graph decomposition (GVY).15