Impact of Wavelength and Modulation Conversion on Transluscent Elastic Optical Networks Using MILP

TL;DR

This paper evaluates how wavelength and modulation conversion technologies impact the efficiency and cost of elastic optical networks, using MILP models and simulations to quantify benefits and improve computational speed.

Contribution

It introduces a MILP formulation for optimal resource allocation and a recursive model to enhance scalability and computation speed in elastic optical networks.

Findings

Systems with wavelength converters use less bandwidth.

Signal regenerators reduce total bandwidth requirements.

Recursive model speeds up computation and improves predictability.

Abstract

Compared to legacy wavelength division multiplexing networks, elastic optical networks (EON) have added flexibility to network deployment and management. EONs can include previously available technology, such as signal regeneration and wavelength conversion, as well as new features such as finer-granularity spectrum assignment and modulation conversion. Yet each added feature adds to the cost of the network. In order to quantify the potential benefit of each technology, we present a link-based mixed-integer linear programming (MILP) formulation to solve the optimal resource allocation problem. We then propose a recursive model in order to either augment existing network deployments or speed up the resource allocation computation time for larger networks with higher traffic demand requirements than can be solved using an MILP. We show through simulation that systems equipped with signal regenerators or wavelength converters require a notably smaller total bandwidth, depending on the topology of the network. We also show that the suboptimal recursive solution speeds up the calculation and makes the running-time more predictable, compared to the optimal MILP.