Davide Cherubini - PhD Thesis - UniCA Eprints

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6.4 LP modelsdecomposed in order to find the explicit LSP to be imposed in each router.For the sake of clarity, in figure 6.3 the solution of the presented model for abenchmark network is shown.Figure 6.3: Example of solutionAt ingress node A the aggregated flow (deficit) is specified, which is equalto the sum of traffic outgoing from nodes C and D. These values are the givencommodities directly obtained from the traffic matrix.Furthermore, for each arc the solution obtained from the model is indicated.Two possible equivalent solutions of the decomposition algorithm are shown infigures 6.4(a) and 6.4(b).In the first solution 3 flows have been obtained, while in the second the initialaggregated flow has been decomposed in 2 flows.In other words, it is possible to obtain multiple equivalent solution while thenumber of LSP paths to be imposed is significantly different.Unfortunately, a path decomposition algorithm that furnishes a unique optimalsolution for these class of problems does not exist in literature and then itis only possible to obtain multiple solutions, which have to be evaluated in orderto fit further explicit requirements of the problem (e.g. minimize the maximumnumber of LSP).59
6.4 LP models(a) 1 st solution(b) 2 nd solutionFigure 6.4: Flow decomposition solutions6.4.2 Model 2The second model pursues the same objective of the first model using IS-IS andcomplementary explicit LSPs. However, in this case, the technique used to guaranteethe network to be survivable is the path restoration and the backup pathis realized using implicit LSPs (obtained from the IS-IS metrics).The data and the variables, as well as the GRP, are essentially identical to thoseof the first model, while the survivability constraint is quite different.For completeness the whole model is reported and its arc-path formulation isgiven.NotationDataN - Node setA - Edge setF - Commodity setc ij - Capacity associated with link (i, j)60
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AcknowledgementsThis dissertation w
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AbstractThis dissertation investiga
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CONTENTS7.4 The Real ISP’s Italia
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LIST OF FIGURES7.3 Default metrics
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1.2 Objectives of the dissertation2
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Chapter 2Basic knowledgeThis chapte
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2.1 Understanding IS-IS• A = sour
Page 19 and 20: 2.2 Understanding MPLS Technology2.
Page 21 and 22: 2.2 Understanding MPLS TechnologyTh
Page 23 and 24: 2.4 Restoration SchemesHowever, fai
Page 26 and 27: 3.1 Optimization of IS-IS/OSPF rout
Page 28: 3.3 Survivability problemhas been d
Page 31 and 32: 4.1 Heuristic Algorithmsmeta-heuris
Page 33 and 34: 4.1 Heuristic Algorithmsto keep a c
Page 35 and 36: 4.1 Heuristic Algorithmsprobability
Page 37 and 38: 4.3 Linear Programming ApproachExam
Page 39 and 40: 5.2 Traffic monitoring• 60% of th
Page 41 and 42: 5.2 Traffic monitoringExporting the
Page 43 and 44: 5.2 Traffic monitoringare included
Page 45 and 46: 5.2 Traffic monitoringthe Internet.
Page 47 and 48: 5.2 Traffic monitoring5.2.3 The net
Page 49 and 50: 5.2 Traffic monitoring5.2.4 Monitor
Page 51 and 52: 5.2 Traffic monitoringFigure 5.9: S
Page 53 and 54: Chapter 6LP Optimization ModelsThis
Page 55 and 56: 6.2 Graphs and Network Flowswith a
Page 57 and 58: 6.2 Graphs and Network FlowsWhere B
Page 59 and 60: 6.2 Graphs and Network Flows6.2.3 T
Page 61 and 62: 6.3 Multicommodity Flow Problemscom
Page 63 and 64: 6.4 LP modelsThe second layer intro
Page 65 and 66: 6.4 LP modelsEquation 6.32 is the o
Page 67 and 68: 6.4 LP modelsmalized as follows:z =
Page 69: 6.4 LP models(a) Rerouting flow p
Page 73 and 74: 6.4 LP models∑f∈Fx f,lij⎛⎝i
Page 75 and 76: 6.4 LP modelsterm is the MPLS part
Page 77 and 78: 7.2 The highly meshed network7.2 Th
Page 79 and 80: 7.3 The IBCN European network7.3 Th
Page 81 and 82: 7.3 The IBCN European networkmaximu
Page 83 and 84: 7.3 The IBCN European networkSurviv
Page 85 and 86: 7.3 The IBCN European networkFigure
Page 87 and 88: 7.4 The Real ISP’s Italian Backbo
Page 93 and 94: 7.5 Conclusion and validation of re
Page 95 and 96: optimal configuration of network pa
Page 97 and 98: REFERENCES[14] Jones Lustig Format
Page 99 and 100: REFERENCES[40] A. V. Fiacco and G.
Page 101: REFERENCES[61] A. Nucci, B. Schroed
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Davide Cherubini - PhD Thesis - UniCA Eprints

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