Online RMLSA in EONs with $A^3G$: Adaptive ACO with Augmentation of Graph

TL;DR

This paper presents an adaptive ACO-based method for joint routing and spectrum assignment in dynamic Elastic Optical Networks, utilizing an auxiliary graph and a novel fitness function to improve resource utilization and reduce blocking.

Contribution

It introduces a constraint-based adaptive ACO approach with an auxiliary graph for joint RMLSA in EONs, enhancing convergence speed and resource efficiency.

Findings

Reduces network fragmentation and blocking probability.

Achieves faster convergence compared to traditional methods.

Improves spectrum utilization in dynamic traffic scenarios.

Abstract

Routing and Spectrum Assignment (RSA) represents a significant challenge within Elastic Optical Networks (EONs), particularly in dynamic traffic scenarios where the network undergoes continuous changes. Integrating multiple modulation formats transforms it into Routing Modulation Level and Spectrum Assignment (RMLSA) problem, thereby making it more challenging. Traditionally, addressing the RSA problem involved identifying a fixed number of paths and subsequently allocating spectrum among them. Numerous heuristic and metaheuristic approaches have been proposed for RSA using this two-step methodology. However, solving for routing and assignment of spectrum independently is not recommended due to their interdependencies and their impact on resource utilization, fragmentation and bandwidth blocking probability. In this paper, we propose a novel approach to solve the RMLSA problem jointly in dynamic traffic scenarios, inspired by Ant Colony Optimization (ACO). This approach involves augmenting the network into an Auxiliary Graph and transforming conventional ACO into a constraint-based ACO variant that adapts to the constraints of EONs. This adaptation also includes an adaptive initiation process and an aggressive termination strategy aimed at achieving faster convergence. Moreover, we have introduced a novel objective/fitness function, to minimize average network fragmentation while ensuring optimal spectrum resource utilization, thereby reducing overall blocking probability.