Davide Cherubini - PhD Thesis - UniCA Eprints

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7.3 The IBCN European networkFigure 7.4: IS-IS optimized metrics under normal conditionFigure 7.5: MPLS optimization under normal condition71
7.3 The IBCN European networkSurvivability optimizationIntroducing the survivability constraints, the obtained results are significantlydifferent, and a detailed discussion is needed. Table 7.5 shows the followingstatements:• in case of single link failure, “default” metrics produce the forecasted congestion;• the IS-IS metaheuristic metrics optimization reduces the objective functionvalue by 26.45% carrying it to the 74.06%. Even if this could seems a goodresult, as the network is always under the congestion level, it is still abovethe empiric threshold of the 70% link occupation.• The MPLS LP model reduces the maximum link occupation by 36.38% withrespect to the “default” metrics and by 13.50% with respect to the IS-ISoptimized metrics. The resulting maximum occupation, in case of failure ofany one link, assumes a value of 64.06%.Phase u max % Gain (Def) % Gain (IS-IS) # LSPDefault u max = 100.7% – – 0IS-IS opt. u max = 74.06% 26.45% – 0MPLS opt. u max = 64.06% 36.38% 13.50% 543Table 7.5: Survivability optimization results for the IBCNThe following figures show in the y-axis the objective function value in caseof failure of the edge indicated in the x-axis.In Figure 7.6, it can be seen that, when edge 15 fails the network suffers acongestion event with a consequent loss of performance. Moreover, when edge 34fails the maximum occupation is over 90%.Figure 7.7 shows the same histogram obtained when the IS-IS metrics have beenoptimized using the metaheuristic procedure, while in Figure 7.8 the results ofthe LP model are depicted. In this latter case, it is important to underline thesmoothness (variance close to zero) of the objective function in case of failure ofone of any of the edge of the network.72
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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
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2.2 Understanding MPLS Technology2.
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2.2 Understanding MPLS TechnologyTh
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2.4 Restoration SchemesHowever, fai
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3.1 Optimization of IS-IS/OSPF rout
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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 and 70: 6.4 LP models(a) Rerouting flow p
Page 71 and 72: 6.4 LP models(a) 1 st solution(b) 2
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
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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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