Incremental optical network topology optimization using meta-mesh span restoration

Kasem, Ahmed Zaky; Doucette, John

doi:10.1109/drcn.2011.6076887

Cited by 2 publications

(3 citation statements)

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“…In most of the work in the literature, the underlying network topology is known in advance, but there have been several approaches developed that include at least some aspects of an unknown or variable topology in the network design process [17][18][19][20]. In [19] and [21], the design methods for tree topologies optimization in communication and data networks did not consider restoration or reliability.…”

Section: Straddling Spans P-cyclementioning

confidence: 99%

“…In [19] and [21], the design methods for tree topologies optimization in communication and data networks did not consider restoration or reliability. In [18,[20][21][22] biconnected network topologies were considered as a transition from tree topologies. In [17][18][19][20], survivability itself was included in the design approach.…”

Section: Straddling Spans P-cyclementioning

confidence: 99%

“…In [18,[20][21][22] biconnected network topologies were considered as a transition from tree topologies. In [17][18][19][20], survivability itself was included in the design approach. In these approaches, fixed costs are typically associated with establishment of a span as well as with placement of working and spare capacity on those spans.…”

Section: Straddling Spans P-cyclementioning

confidence: 99%

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ILP Model and Relaxation-Based Decomposition Approach for Incremental Topology Optimization inp-Cycle Networks

Noor‐E‐Alam

Kasem

Doucette

2012

Journal of Computer Networks and Communications

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p-cycle networks have attracted a considerable interest in the network survivability literature in recent years. However, most of the existing work assumes a known network topology upon which to apply p-cycle restoration. In the present work, we develop an incremental topology optimization ILP for p-cycle network design, where a known topology can be amended with new fibre links selected from a set of eligible spans. The ILP proves to be relatively easy to solve for small test case instances but becomes computationally intensive on larger networks. We then follow with a relaxation-based decomposition approach to overcome this challenge. The decomposition approach significantly reduces computational complexity of the problem, allowing the ILP to be solved in reasonable time with no statistically significant impact on solution optimality.

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