Optimisation of passive optical network design under demand uncertainty
Abstract
The Passive Optical Network (PON) is a point-to-multipoint, optical fibre telecommunication
network used at the access level, in which a signal is distributed via a
single fibre from the Central Office (CO) to a number of downstream Optical Network
Units (ONUs) at customer premises. In addition to sharing a single fibre between
a number of customers, these networks use passive components in the field,
providing future-proof networks with no electricity requirements. All these benefits,
together with high bandwidth potential, makes PONs and, in particular, the ITU-T
G.984 Gigabit Passive Optical Network (GPON), the access network of choice for service
providers. Traditionally planned by hand, advanced methods have been developed to design
PON deployments, including heuristics, meta-heuristics and exact mathematical models.
Unfortunately, heuristic methods provide sub-optimal solutions, which, due to
high deployment costs in general, result in high and unnecessary overhead. Conversely,
exact mathematical models of the Passive Optical Network Design Problem
(PONDP) can give optimal, minimum cost solutions, but are very demanding in terms
of computational effort, limiting the size of networks that can be solved in an acceptable
time period. Furthermore, since PONs are mostly deployed in a greenfield setting,
customer demand is uncertain, complicating the design of an accurate model even
more. This thesis addresses two concerns in the exact mathematical modelling framework:
model accuracy and computational tractability. To improve computational performance,
a row- and column generation approach based on Benders decomposition is
provided, strengthened by additional cut separation algorithms. This approach is
found to be much more scalable and flexible than the classical arc flow approach when
accounting for physical network constraints inherent in the PON specifications, due
to the efficient handling of path length constraints. Furthermore, the framework presented
contributes towards general hierarchical network connectivity problems with path length constraints, which have not been studied extensively in literature, and
its flexibility is demonstrated by means of a number of model refinements, including
the addition of different splitter types, edge-disjoint survivability between the CO and
splitters, and homo- and heterogeneous multi-level networks. To address demand uncertainty,
two distinct approaches are followed, resulting in a two-stage recourse and a
robust formulation. These both serve to lower cost through optical fibre and splitter dimensioning
while ensuring a minimum level of connectivity. A revenue-based model
is formulated in conjunction with the stochastic formulations to illustrate the impact
of directly maximising return on investment. Finally, the methods are verified and validated using cross-model verification, an external
feasibility checker and face validation, before ensuring all network parameters
conform to the G.984 specification, resulting in a practically feasible network design
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