Efficient Mixed Integer Linear Programming Approaches to Dynamic Path Restoration

TL;DR

This paper develops an efficient mixed integer linear programming model for dynamic path restoration in elastic optical networks, addressing the NP-hard problem of rerouting after link failures while considering length constraints.

Contribution

It introduces a comprehensive MILP model that handles link restoration, wavelength, and spectrum assignment, with a preprocessing step to improve computational efficiency.

Findings

Model accurately determines restoration feasibility without extra regenerators.

Preprocessing significantly reduces solution time.

Model applies to both link restoration and spectrum assignment problems.

Abstract

We consider the problem of single link failure in an elastic optical network, (also known as flex-grid WDM network). The task is to reroute optical connections that go through the broken link using free capacity of other links of the network. Nowadays, dynamic restoration gains popularity, in which the possiblity of rerouting is only inspected after a link failure is detected. Since the problem of recovery is NP-hard, heuristic algorithms are used to either find such routes, or suggest that the routes do not exist. In order to understand the quality of these heuristics, often mixed integer linear programming is used to obtain exact positive and negative answers. We present a detailed such model that checks whether restoration is possible without the use of additional regenerators. This means, that the new light paths need to satisfy a length constraint. As preprossing we apply a trimming procedure that takes advantage of this length constraint, and significantly speeds up the evaluation of these models. Our model is more general, and besides solving the problem of link restoration, also solves the full problem of wavelength and spectrum assignment.