Abstract
We consider an elastic optical network and study the static routing and spectrum assignment
(RSA) problem aiming to minimize the maximum number of frequency slots required to accommodate all
lightpath demands. We introduce a novel node-arc integer linear programming (ILP) model, which
jointly decides optimal routes and assigned spectra for lightpaths between all source–destination
pairs. To reduce the total number of variables, and therefore lower the computational complexity,
our new node-arc model extends previous work by representing the spectrum assigned to each
lightpath by two variables (i.e., the starting and ending boundary frequency slot indexes). To
achieve scalability, we also develop an efficient spectrum-window-based greedy heuristic
algorithm, and further propose three multiiteration-based algorithms that consider the effect of
demand-serving sequences. Analytical and numerical results show that comparing with an existing
approach, our solution to the RSA problem based on the new node-arc ILP model achieves a
significant computational complexity improvement. Further numerical results demonstrate that the
proposed multiiteration algorithms obtain solutions closer to optima than existing
algorithms.
© 2013 IEEE
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