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# Optimizing GIS based Systems

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GIS based systems can be optimized to work better than ever. And this PowerPoint presentation has a few of the ways to show the same

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### Optimizing GIS based Systems

1. 1. 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) http://www.adcorporations.com
2. 2. Topics Covered Geographical Information Systems (GIS) <ul><li>Conflation of Vector Buildings with Imagery </li></ul><ul><li>Automatic Metro Map Layout using Multicriteria Optimization </li></ul><ul><li>Geo-Opportunistic Routing for Vehicular Networks </li></ul>http://www.adcorporations.com
3. 3. Conflation of Vector Buildings with Imagery Geographical Information Systems (GIS) <ul><li>Conflation:- </li></ul><ul><ul><li>Literal Meaning: The process or result of fusing items into one entity; fusion; amalgamation. </li></ul></ul><ul><ul><li>Verb: to combine or blend (two things, esp. two versions of a text or two images) so as to form a whole </li></ul></ul><ul><li>2. Clique:- here means to be looking as a single unit but which is not. </li></ul><ul><li>3. Solution:- Mathematics can solve this problem! </li></ul>http://www.adcorporations.com
4. 4. Solution Geographical 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) & MapMerger As 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 Python http://www.adcorporations.com
5. 5. CONFLATION Conflation Process Geographical Information Systems (GIS) http://www.adcorporations.com
6. 6. Automatic Metro Map Layout using Multicriteria Optimization Geographical Information Systems (GIS) Fig. Metro map features. http://www.adcorporations.com
7. 7. (a) optimal angular resolution and (b) poor angular resolution. Geographical Information Systems (GIS) http://www.adcorporations.com
8. 8. Octilinearity Geographical Information Systems (GIS) http://www.adcorporations.com
9. 9. Table: Octilinearity Criterion Geographical Information Systems (GIS) http://www.adcorporations.com
10. 10. (a) poor line straightness and (b) improved line straightness. Geographical Information Systems (GIS) http://www.adcorporations.com
11. 11. Enforcement of the relative positions when moving a station. Geographical Information Systems (GIS) The gray-shaded area shows the degree of freedom afforded to (a) station A and (b) station C. http://www.adcorporations.com
12. 12. Preservation of edge ordering. Geographical Information Systems (GIS) Without preserving the ordering of edges, station C would be able to move as shown, changing the topology of the map. http://www.adcorporations.com
13. 13. Label Criteria Geographical Information Systems (GIS) Search space for labeling the metro map. http://www.adcorporations.com
14. 14. Label Criteria Geographical Information Systems (GIS) Label position consistency. Label position consistency. (Not Observed here) http://www.adcorporations.com
15. 15. Label Criteria Geographical Information Systems (GIS) An example of ambiguous labeling. http://www.adcorporations.com
16. 16. Label Criteria Geographical Information Systems (GIS) (a) perpendicular tick labels and (b) nonperpendicular tick labels. http://www.adcorporations.com
17. 17. Clustering Geographical Information Systems (GIS) Clustering multiple overlength edges. The edges AE and BC are (a) too long and it is only possible to reduce the length of these edges by moving stations C, D, and E (b) at the same time. http://www.adcorporations.com
18. 18. Clustering Geographical Information Systems (GIS) Clustering stations to find nonstraight lines. Ultimately, six clusters will be identified in this graph: (BC), (CD), (DE), (GH), (HI), and (IJK). http://www.adcorporations.com
19. 19. Example & Trial of the System Geographical 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) http://www.adcorporations.com
20. 20. Example & Trial of the System Geographical Information Systems (GIS) Mexico City map: official layout. http://www.adcorporations.com
21. 21. Example & Trial of the System Geographical Information Systems (GIS) Mexico City map: official layout, normalized to the layout software style. http://www.adcorporations.com
22. 22. Example & Trial of the System Geographical Information Systems (GIS) Mexico City map: undistorted layout. http://www.adcorporations.com
23. 23. Example & Trial of the System Geographical Information Systems (GIS) Mexico City map: Author`s Layout. http://www.adcorporations.com
24. 24. Example & Trial of the System Geographical Information Systems (GIS) http://www.adcorporations.com
25. 25. Geo-Opportunistic Routing for Vehicular Networks Geographical Information Systems (GIS) 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. http://www.adcorporations.com
26. 26. Geo-Opportunistic Routing for Vehicular Networks Geographical Information Systems (GIS) <ul><li>So Called Efficient multihop routing in a Vehicular Ad hoc Network (VANET) Fails for following reasons </li></ul><ul><li>It is a highly distributed self-organizing network formed by moving vehicles that are characterized by very high mobility yet constrained by roads. </li></ul><ul><li>Its size can scale up to hundreds of thousands of nodes. </li></ul><ul><li>Nodes could suffer from severe wireless channel fading due to motion and obstructions in urban environments (e.g., building, trees, and vehicles). </li></ul><ul><li>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. </li></ul><ul><li>Therefore, we cannot directly use those protocols to support </li></ul><ul><li>such emerging vehicular applications. </li></ul>http://www.adcorporations.com
27. 27. Solution Geographical Information Systems (GIS) <ul><li>Existing geographic routing protocols such as GPCR(Geographic Perimeter Coordinate Routing) & GPSR(Geographic Perimeter Stateless Routing) that address the unreliable channels using </li></ul><ul><li>opportunistic forwarding (GeRaF) & (CBF) </li></ul>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. <ul><li>Geographic routing is preferable in a VANET for the following reasons , </li></ul><ul><li>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. </li></ul><ul><li>It is becoming easier to support geographic routing as GPS-based navigation systems are getting cheaper and becoming a common add-on. </li></ul>http://www.adcorporations.com
28. 28. Solution Geographical Information Systems (GIS) 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 http://www.adcorporations.com
29. 29. Opportunistic Routing Geographical Information Systems (GIS) Dashed arrows are GpsrJ+ and solid arrows are GPCR. http://www.adcorporations.com
30. 30. TO-GO DESIGN Geographical 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. http://www.adcorporations.com
31. 31. FSS Geographical 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. http://www.adcorporations.com
32. 32. FSS Analysis Geographical 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(n 2 ) where n is the number of C’s neighbours. http://www.adcorporations.com
33. 33. Uses & Applications Geographical Information Systems (GIS) <ul><li>Oceania engineers in coastal calculations, </li></ul><ul><li>Sewage System Planning, and Civil Engineering Applications. </li></ul><ul><li>50 Year future Planning, </li></ul><ul><li>Architectural Development, </li></ul><ul><li>Map corrections and Improvements. </li></ul><ul><li>Vehicular Networks, </li></ul><ul><li>Traffic Management, </li></ul><ul><li>Emergency Alerts, </li></ul><ul><li>Dynamic & Automatic Map Creation, </li></ul><ul><li>Information Exchange, </li></ul><ul><li>Tracking of the Race tracks by Co-Pilot. </li></ul><ul><li>All the above mentioned uses and Applications can be implemented to provide Output better than the desired </li></ul><ul><li>one by a small change in the Algorithm. The system </li></ul><ul><li>will work in an Optimized manner. </li></ul>http://www.adcorporations.com
34. 34. Conclusions Geographical Information Systems (GIS) <ul><li>A. Conflation </li></ul><ul><li>Conflation is a Prior requisite to clear the issues like errors in the maps and cliques to be removed. </li></ul><ul><li>B. Automatic Metro Map Layout using Multicriteria Optimization </li></ul><ul><li>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. </li></ul><ul><li>C. Geo-Opportunistic Routing for Vehicular Networks </li></ul><ul><li>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. </li></ul><ul><li>I hereby Conclude that these systems we have seen </li></ul><ul><li>until now is just a beginning and a lot of development </li></ul><ul><li>can be done in the area. The authors have come up </li></ul><ul><li>with intuitive and exceptional new ideas and have </li></ul><ul><li>also implemented them. </li></ul>http://www.adcorporations.com
35. 35. References Geographical 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: 101-114 1077-2626/11/   [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/ http://www.adcorporations.com
36. 36. Any Questions? Geographical Information Systems (GIS) http://www.adcorporations.com
37. 37. Thanks a lot ! For this Opportunity Geographical Information Systems (GIS) http://www.adcorporations.com
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