Heuristic Chaotic Hurricane-Aided Efficient Power Assignment for Elastic Optical Network

Layhon R Rodrigues Dos Santos,Taufik Abrao

doi:10.1109/access.2020.2991417

Abstract

In this paper, we propose a dynamical power allocation (PA) procedure for elastic optical networks (EONs) based on the evolutionary hurricane search optimization (HSO) algorithm with a chaotic logistic map diversification strategy with the purpose of improving the capability to escape from local optima, namely PA-CHSO. The aiming is the dynamical control of the transmitted optical powers according to the variations of each link state due to traffic fluctuations, channel impairments, as well as other channel-power coupling effects. Such realistic EON scenarios are affected mainly by the channel estimation inaccuracy, channel ageing and power fluctuations. The link state is based on the channel estimation and quality of transmission (QoT) parameters obtained from the optical performance monitors (OPMs). Numerical results have demonstrated the effectiveness of the PA-CHSO to dynamically mitigate the power penalty under real measurement conditions with uncertainties and noise, as well as when perturbations in the optical transmit powers are considered.

Highlights

The growth of the traffic demand with heterogeneous characteristics associated to the increment of the SNR rate requirements has pressing the development of dynamical optical networks
The best knowledge of the quality of transmission (QoT) is needed in the design and operation phases, owing to the margin has to be added in the network when the QoT is not well established [4]
The findings reported in the previous papers assume that there are no impact of queuing issues on the optical network convergence and performance

Summary

INTRODUCTION

The growth of the traffic demand with heterogeneous characteristics associated to the increment of the SNR rate requirements has pressing the development of dynamical optical networks. The HSO was considered as a promising alternative algorithm for solving problems in practical large-scale power systems [19] In this context, the contributions of this work include: a) proposing an effective, efficient PA strategy based on the HSO and its variation based on the insertion of a chaotic map, named PA-HSO and -CHSO, respectively; b) investigating systematically the input parameter optimization (IPO) for both PA algorithms, aiming at improving the performance-complexity tradeoff of the proposed algorithm; c) validating both PA algorithms for different realistic EON channel conditions, i.e., non-perfect monitoring of the OPMs, channel ageing effects, dynamical scenarios, including power instability, in EONs. comparisons have been performed assuming a convex optimization through the gradient descent (GD) [14], [15]. To corroborate the effectiveness and efficiency of the proposed resource allocation strategy in EONs, it is evaluated: normalized mean square error (NMSE); convergence; power penalty (PP); probability of success; CC; and performance-complexity tradeoff

PROPOSED SCHEME

PA SCHEMES

PA-CHSO

NUMERICAL RESULTS

CONCLUSION