Algorithms for the visualization and simulation of mobile ad hoc and ...

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21in size so that they are easily visible when the view is zoomed out. This feature isillustrated in Figures 2.15.(a)(b)Figure 2.15: (a) shows the nodes and edges at normal size. (b) shows the nodes andedges scaled up for better visibility.2.5 ConclusionIn this chapter we have discussed two network visualization techniques that havebeen implemented in the OMAN ad hoc wireless network simulator. First, we haveshown a method for providing a visual representation of the signal radiation patternsof transmitting nodes. Along with this we have provided a visual representation ofthe regions of acceptably high SINR that allows a feasible channel to exist. Each ofthese visualizations are done for both certain and uncertain environments. Throughthese visualizations we can gain a better understanding of how parameter selectionand resource allocation can affect the design of mobile ad hoc networks.Our second visualization presented is the use of digital terrain data to improvethe visualization of network simulation results. We started by discussing the terrain
22library that was implemented in support of adding digital terrain data into OMAN.With that we then discussed the different 2D and 3D visualization options this thenadded to OMAN. Overall the addition of digital terrain to the visualization of mobilead hoc networks adds another dimension of reality and understanding to the simulatedresults. We are able to better understand the effects that terrain has on the simulatednetworks when we are able to see the network on the actual terrain.2.6 Future WorkIn future work we hope to develop further methods of meaningfully visualizingother layers of the network model. The integration of different visualizations togetherwould also be a worth while exploration. The display of the signal radiation patternsoverlayed onto the 3D display of the network with its terrain could help to revealfurther information about the simulation results. We would also like to further developthe interactivity of the 3D displays.
Page 2 and 3: c○ Copyright 2009Daniel Hennessey
Page 4 and 5: iiiTable of ContentsList of Tables
Page 6 and 7: vList of Tables3.1 This table lists
Page 8 and 9: vii2.12 Figures showing OMAN networ
Page 10: ixAbstractAlgorithms for the Visual
Page 13 and 14: 2provement of the simulations. Chap
Page 15 and 16: 4on the clarity, quality, and richn
Page 17 and 18: 6(a)(b)Figure 2.1: Signal radiation
Page 19 and 20: 8(a)(b)Figure 2.3: Acceptable SINR
Page 21 and 22: 10Terrain ClassThe Terrain class is
Page 23 and 24: 12hull operation. In Figure 2.7 the
Page 25 and 26: 14TerrainResolutionChanger ClassDif
Page 27 and 28: 16objects are collapsed together in
Page 29 and 30: 18its results. An example of this w
Page 31: 20(a)(b)(c)(d)Figure 2.14: Figures
Page 35 and 36: 24connected at the outset, we ensur
Page 37 and 38: 26types of graph data. Our goal is
Page 39 and 40: 28metric is similar to the shortest
Page 41 and 42: 30cause the graph to fragment. In o
Page 43 and 44: 323.5 Metric Performance CriteriaOn
Page 45 and 46: # Nodes200 600 1000 Citation 800 12
Page 47 and 48: 36(a)(b)(c)(d)Figure 3.3: Citation
Page 49 and 50: 38(a)(b)(c)(d)Figure 3.5: Citation
Page 51 and 52: 40(a)(b)(c)(d)Figure 3.6: Inet grap
Page 53 and 54: 42(a)(b)(c)(d)Figure 3.8: Inet grap
Page 55 and 56: 44(a)(b)(c)(d)Figure 3.10: Inet gra
Page 57 and 58: 46(a)(b)(c)(d)Figure 3.12: Inet gra
Page 59 and 60: 48sensing algorithms.This chapter i
Page 61 and 62: 50Figure 4.1: Basic diagrams compar
Page 63 and 64: 52Figure 4.3: Graph showing a compa
Page 65 and 66: 54part to the lack of a capable hig
Page 67 and 68: 56in [44]. This method breaks the s
Page 69 and 70: 58L ≤ N ′ /4 in order to provid
Page 71 and 72: 604.5.2 Test DataIn testing the imp
Page 73 and 74: 62MatlabM 512 1024 2048 409625% Ove
Page 75 and 76: 644.6.2 FFT Accumulation MethodThe
Page 77 and 78: 66CUDAN 1024 2048 4096 8192Memory T
Page 79 and 80: 684.7 ConclusionThe computational c
Page 81 and 82: 70Bibliography[1] Ravindra K. Ahuja
Page 83 and 84:
72[25] M.Y. Kao, N. Occhiogrosso, a
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