optimizing gis based systems

OPTIMIZING CONFLATION, AUTOMATIC MAP LAYOUT AND

GEO-OPPORTUNISITIC ROUTING IN VEHICULAR NETWORKS

Submitted by:Ajinkya Deshpande | R No. 3519

Guided by:Prof. G. P. Potdar

Geographical Information Systems (GIS)

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Topics Covered


1. Conflation of Vector Buildings with Imagery

2. Automatic Metro Map Layout using Multicriteria

Optimization

3. Geo-Opportunistic Routing for Vehicular Networks

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Conflation of Vector Buildings with Imagery


1. Conflation:- • Literal Meaning: The process or result of fusing items into one

entity; fusion; amalgamation. • Verb: to combine or blend (two things, esp. two versions of a

text or two images) so as to form a whole

2. Clique:- here means to be looking as a single unit but which is

not.

3. Solution:- Mathematics can solve this problem!3



SolutionGeographical Information Systems (GIS)

Solution:- Mathematics can solve this problem!A large solution set is provided here,We will use,

ArcView by ESRI (I used ArcGIS Desktop 10)

&

MapMergerAs our tools to apply the Mathematical solutions for the Conflation Process

The above two softwares are capable of using a large set MATLAB code and also C Codes with the help

of VB.Net and other support tools as Python4




CONFLATION

Conflation Process


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Automatic Metro Map Layout using Multicriteria Optimization


Fig. Metro map features.6



(a) optimal angular resolution and (b) poor angular resolution.


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Octilinearity


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Table: Octilinearity Criterion

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(a) poor line straightness and (b) improved line straightness.

10 http://www.adcorporations.com



Enforcement of the relative positions when moving a station.

The gray-shaded area shows the degree of freedom afforded to (a) station A and (b) station C.

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Preservation of edge ordering.

Without preserving the ordering of edges, station C would be able to move as shown, changing the topology of the map.12




Label Criteria

Search space for labeling the metro map.

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Label Criteria

Label position consistency. Label position consistency.

(Not Observed here)14




Label Criteria

An example of ambiguous labeling.

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Label Criteria

(a) perpendicular tick labels and (b) nonperpendicular tick labels.16




Clustering

Clustering multiple overlength edges. The edges AE and BCare (a) too long and it is only possible to reduce the length of theseedges by moving stations C, D, and E (b) at the same time.

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Clustering

Clustering stations to find nonstraight lines. Ultimately, sixclusters will be identified in this graph: (BC), (CD), (DE), (GH),(HI), and (IJK).

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Example & Trial of the SystemGeographical Information Systems (GIS)

The time taken to generate the automatically generated maps discussed in this paper is given in Table. These timings were performed in Java 1.6, on a computer with a 1.4 GHz Celeron M processor, 1.5 GB RAM, and running Windows XP. The values are the average of three runs. All maps (automatically generated, published, and undistorted)

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Mexico City map: official layout.20




Mexico City map: official layout, normalized to the layoutsoftware style.21




Mexico City map: undistorted layout.22




Mexico City map: Author`s Layout.23




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Geo-Opportunistic Routing forVehicular Networks


One of the recent outcomes is a novel wireless architecture called Wireless Access for the Vehicular Environment (WAVE) that provides short-range intervehicular communications to enable fast dissemination of emergency related messages.

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Geo-Opportunistic Routing forVehicular Networks


So Called Efficient multihop routing in a Vehicular Ad hoc Network (VANET) Fails for following reasons 1.It is a highly distributed self-organizing network formed by moving vehicles that are characterized by very high mobility yet constrained by roads. 2.Its size can scale up to hundreds of thousands of nodes. 3.Nodes could suffer from severe wireless channel fading due to motion and obstructions in urban environments (e.g., building, trees, and vehicles). 4. The vehicle density changes over time (rush hours), and the distribution of vehicles is non-uniform due to various road widths and skewed popularity of roads. Under this circumstance, most ad hoc routing protocols that discover and maintain end-to-end paths (e.g., Ad Hoc On Demand Vector [AODV], Dynamic Source Routing [DSR]) are less preferable due to high protocol overheads.

Therefore, we cannot directly use those protocols to support such emerging vehicular applications. 26


Solution


Existing geographic routing protocols such as GPCR(Geographic Perimeter Coordinate Routing) & GPSR(Geographic Perimeter Stateless Routing) that address the unreliable channels using

opportunistic forwarding (GeRaF) & (CBF)To remedy this problem, The Authors propose TOpology-assisted Geo-Opportunistic routing (TO-GO), that incorporates road topology information into the forwarding set selection to better exploit the benefit of opportunistic forwarding.

Geographic routing is preferable in a VANET for the following reasons, 1.Geographic routing is stateless; it neither exchanges link state information nor maintains established routes as in conventional mobile ad hoc routing protocols. The exchange and route maintenance are very costly in highly mobile vehicular environments. 2.It is becoming easier to support geographic routing as GPS-based navigation systems are getting cheaper and becoming a common add-on.

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Solution


One of the popular routing protocols in a VANET is geographic routing.

A packet is greedily forwarded to a neighbouring node whose distance toward the packet’s destination is closer than that of the current node

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Opportunistic RoutingGeographical Information Systems (GIS)

Dashed arrows are GpsrJ+ and solid arrows are GPCR.29


TO-GO DESIGNGeographical Information Systems (GIS)

The Next-hop Prediction Algorithm (NPA), which determines a packet’s target node; the Forwarding Set Selection (FSS) algorithm, which finds a set of candidate forwarding nodes; and the priority scheduling method, which suppresses redundant packet transmissions based on a distance based timer.

The lens shaped area is the forwarding region established between source and destination nodes in existing schemes, and between the source and the furthest node on the current road segment (called target node) in TO-GO: a) existing schemes; b) TO-GO. 30


FSSGeographical Information Systems (GIS)

Forwarding set selection approximation: a) shaded region contains neighbors of C that can hear both C and T; b) shaded region contains neighbors of C that can hear both M and T, and can also hear each other.

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FSS AnalysisGeographical Information Systems (GIS)

A brute force algorithm to find a forwarding set in which nodes hear one another is analogous to finding a maximal clique in which every node has a connection to every other node. Such a problem is NP-complete.

SOLUTION:-

By continue adding N until all the neighbours of C have been checked, we can find a opportunistic forwarding set. The algorithm takes,

O(n2)

where n is the number of C’s neighbours.

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Uses & ApplicationsGeographical Information Systems (GIS)

• Oceania engineers in coastal calculations,• Sewage System Planning, and Civil Engineering Applications.• 50 Year future Planning,• Architectural Development,• Map corrections and Improvements.

o Vehicular Networks,o Traffic Management,o Emergency Alerts,o Dynamic & Automatic Map Creation,o Information Exchange,o Tracking of the Race tracks by Co-Pilot.

All the above mentioned uses and Applications can be implemented to provide Output better than the desiredone by a small change in the Algorithm. The system will work in an Optimized manner.33


ConclusionsGeographical Information Systems (GIS)

A. Conflation• Conflation is a Prior requisite to clear the issues like errors in

the maps and cliques to be removed.

B. Automatic Metro Map Layout using Multicriteria Optimization• Optimizing Multiple Criterion in Metro Map Layout as well as

any other Automatic Mapping System can lead to best formed Maps those could be understood and used accurately.

C. Geo-Opportunistic Routing for Vehicular Networks• This is just the beginning in Vehicular Networks a large

development is yet to come a no. of Protocols are being exploited to give rise to better protocols.

― I hereby Conclude that these systems we have seenuntil now is just a beginning and a lot of development can be done in the area. The authors have come upwith intuitive and exceptional new ideas and have also implemented them.

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ReferencesGeographical Information Systems (GIS)

[01] Jonathan Stott, Peter Rodgers, Juan Carlos Martı´nez-Ovando, and Stephen G. Walker – “Automatic Metro Map Layout Using Multicriteria Optimization” IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL. 17, NO. 1, JANUARY 2011 Pages: 101-1141077-2626/11/ [02] Isaac Sledge, Student Member, IEEE, James Keller, Fellow, IEEE, Wenbo Song, and Curt Davis, Fellow, IEEE – “Conflation of Vector Buildings With Imagery” IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 8, NO. 1 JANUARY 2011 Pages: 83-87.1545-598X/ [03] Kevin C. Lee, Uichin Lee, Mario Gerla – “Geo-Opportunistic Routing for Vehicular Networks” IEEE Communications Magazine • May 2010 Pages: 164-170 0163-6804/10/


Any Questions?



Thanks a lot !

For this Opportunity


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