List of Figures

1. The Overview of the Architecture.
2. The Modeling Environment.
3. TGIF - TANGRAM Graphic Interface Facility
4. Template to define a new object type.
5. The Analytical Solvers.
6. The Main Screen
7. The Modeling Environment Module
8. TGIF - TANGRAM Graphic Interface Facility
9. Template to define a new object type.
10. The packet_source object type.
11. Single and Broadcast links.
12. The M/M/1/k model.
13. The Mathematical Model Module.
14. Steady State Analytical Methods.
15. The Measures of Interest Module.
16. The plot generated by the PMF Module.
17. The plot generated by the PMF Module.
18. The plot generated by the PMF Module.
19. The model with Rewards
20. The Simulation Module
21. Triggering on a c.r.
22. Illustration of bound affecting rewards.
23. File distribution trace format
24. The Batch Simulation Module
25. Reward Options Window
26. The Interactive Simulation Module.
27. The box used to control interactive simulation
28. TGIF interface - Progress Indicator - Interactive simulation
29. On-Off source.
30. 3-state MMFS source
31. Channel
32. Sink
33. server_queue - FIFO
34. server_queue - GPS-CS
35. server_queue - GPS-CP
36. server_queue - GPS-CP
37. The Stationary Exact Methods.
38. The Stationary Iterative Methods.
39. Non-Markovian Models.
40. The Transient Methods.
41. Point Probabilities Interface - Uniformization Technique.
42. Point Probabilities Interface - Approximation Technique (Direct).
43. Point Probabilities Interface - Approximation Technique (Iterative).
44. Cumulative Reward Distribution Interface
45. Cumulative Operational Time Distribution Interface
46. Expected Cumulative Rate Reward Interface - Uniformization Technique.
47. Expected Cumulative Rate Reward Interface - Approximation Technique.
48. Expected Cumulative Rate Reward Interface - Approximation Technique.
49. Expected Cumulative Impulse Reward Interface - Uniformization Technique.
50. The Matrix Visualization - States Permutation Interface.
51. The Matrix Visualization Interface.
52. Interface to obtain traffic statistics from a trace
53. Interface to obtain traffic statistics from a markovian model
54. Interface of Tangram-II to CAC algorithms
55. Interface Tangram-II to Traffic Generator.
56. Tangram-II Traffic Generator Structure.
57. Generation mode - min
58. Generation mode - max
59. Interface of Tangram-II to IP traffic measures
60. Interface of Tangram-II to Plot statistics measures
61. Interface of Tangram-II to Histogram genaration and MSE estimation
62. PMF of loss (A) and success (B) of videos packets.
63. Delay calculation of probes generation
64. Round Trip Delay from packets generated at the same instant
65. Comparison between Delay calculations: (A) PMF, (B) CDF.
66. Estimating distribution of delay tried by probes
67. Opening Tangram-II's Model Specification Module
68. Tangram-II's Markov Chain object.
69. (a)Tangram-II model with the Markov_Chain object, and (b) the partial upper-level Markov chain created with it.
70. (a)Tangram-II model created. (b)Hierarchical Gilbert hidden Markov model build with the model of (a).
71. Mathematical Model Generation Module (a) selection button; (b) state space generation interface.
72. HMM Module (a) selection button; (b) model selection interface.
73. HMM Module (a) state variable selection interface; (b) additional parameter specification interface.
74. HMM Module (a) method's and algorithm's interface; (b) chain structure visualization.
75. The MMPP Model
76. The Point Probabilities Method.
77. The Buffer size PMF
78. The Deterministic Server Model
79. The Outputqueueing Model
80. The Measures of Interest module.
81. The PMF of the Switch_2x2.queue_1 object.
82. The Traffic Model.
83. Set Cumulative Rewards Values.
84. The Packet Source object (Set Cumulative Rewards Values).
85. The Server Queue object(Set Cumulative Rewards Values).
86. Event Cloning Model.
87. The ON_OFF Source object (Event Cloning Model).
88. The Infinite_Server object (Event Cloning Model).
89. The Multiple Action Model.
90. The Poisson Source object (Multiple Action Model).
91. The Split object (Multiple Action Model).
92. The Queue object (Multiple Action Model).
93. The MM1k Model with Symbolic Parameters.
94. The Symbolic Parameters Window.
95. The Gated Queueing Vacation Model.
96. The Gated Queue object (Gated Queueing Vacation Model).
97. The Token Parser object (Gated Queueing Vacation Model).
98. The Vector Variable Model.
99. The Poisson Source object (Vector Variable Model).
100. The Queue object (Vector Variable Model).
101. The Simulation Model with Animation.
102. The Availability Model.
103. The System_1 object (Availability Model).
104. The Database Model.
105. The Processor object (Database Model).
106. The Repair object (Database Model).
107. The Database object (Database Model).
108. The Go Back N Model.
109. The Sender object (Go Back N Model) Model 1.
110. The Channel object (Go Back N Model). Model 1
111. The Receiver object (Go Back N Model) Model 1.
112. The Multiplex Channel Model.
113. The Queue Object.
114. The Geometric bulk arrivals model.
115. The Geometric_Bulk object.
116. The recursion tree generated by Geometric_Bulk object from the initial state.
117. The Binomial bulk arrivals model.
118. The Binomial_Bulk object.
119. The Binomial bulk generation process from the initial state.
120. Transitions generated by the arrival event at the initial state.
121. TGWB: Tangram Whiteboard interface.
122. mcastproxy environment example
123. MTK block architecture
124. MTK interfaces: (a) shell interface; (b) graphical interface.
125. Example of a hierarchical HMM with 3 hidden states, in which a Gilbert Markov chain is associated with each hidden state.
126. Example of a hierarchical general HMM with 2 hidden states and 4 observation symbols.
127. Example of a hierarchical general HMM with variable batch size, $2$ hidden states and $4$ observation symbols. Notice the absorbing state, which is identified by the dashed dark circle.