Optimization of OSPF Link Weight to Minimize Worst-Case Network Congestion against Single-Link Failure

Kamrul, Islam Mohammad; Oki, Eiji

doi:10.1109/icc.2011.5963219

Cited by 15 publications

(7 citation statements)

References 13 publications

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“…4. Networks 1–3 mirror the typical backbone networks used to evaluate the routing performance in both [7, 10]. Network 4 is the Abilene network [16] and Network 5 is the National Science Foundation network [17].…”

Section: Performance Evaluationmentioning

confidence: 99%

“…The values of a i and b i are set to the sum of link capacities of the links connected to node i . C max is set to 100, as it needs to exceed the maximum number of links in our examined networks [7]. The simulation program is coded in C language on a Linux computer with 4GB of RAM and an AMD Phenom II X6 processor.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…Kamrul et al [7][8][9] introduced a link weight optimisation policy called preventive start-time optimisation (PSO) where the traffic matrix is exactly known. This traffic model is called a pipe model.…”

Section: Introductionmentioning

confidence: 99%

“…However, it is difficult for the network operators to measure or predict the actual traffic requirement from each node to all the other nodes. How to implement the PSO when the traffic matrix is not exactly known is not discussed in [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

“…The PSO policy in [7] has been applied only to the pipe model, where the traffic matrix is given and all the possible single link failure scenarios are considered. In [10], the traffic matrices are specified by the hose model and link failure is not considered to obtain an optimal link weight set.…”

Section: Introductionmentioning

confidence: 99%

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Preventive start‐time optimisation of open shortest path first link weights for hose model

Ranaweera

Kamrul²,

Oki

2014

IET Networks

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Optimising link weights in an open shortest path first network is a challenging traffic engineering problem to reduce network congestion. Most of the previous studies have focused on the application of start-time optimisation (SO) and run-time optimisation on both pipe and hose models of link weight optimisation. In a more recent study, an efficient policy, preventive start-time optimisation (PSO), has been introduced for link weight optimisation. However, no studies have been reported on the application of PSO to the hose model where the exact traffic demand between each source and destination node pair does not need to be specified. A PSO policy for the hose model to optimise the link weights against link failures is proposed. The proposed scheme employs a heuristic algorithm to determine a suitable set of link weights to reduce worst-case congestion for any single link failure. It efficiently selects the worst-case performance traffic matrix and reduces the worst-case congestion ratio as compared with a brute-force scheme which is computationally expensive when searching the link weight space against all the possible traffic matrices and topologies created by single link failures. The numerical results show that the proposed scheme is more effective in the reduction of worst-case congestion ratio than the scheme utilising SO.

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Section: Performance Evaluationmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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