RMCSA Algorithm for Congestion-Aware and Service Latency Aware Dynamic Service Provisioning in Software-Defined SDM-EONs

TL;DR

This paper introduces a congestion-aware and latency-efficient dynamic routing algorithm for optical networks in 5G/6G, improving resource utilization and reducing blocking and delay through real-time metrics and caching strategies.

Contribution

It proposes a novel RMCSA algorithm that dynamically finds alternative paths based on real-time link occupancy, reducing congestion hotspots and service delay in SDM-EONs.

Findings

Outperforms benchmark algorithms in blocking ratio and spectrum utilization

Reduces service delay significantly with a novel caching strategy

Effectively minimizes congestion hotspots in network simulations

Abstract

The implementation of 5G and the future deployment of 6G necessitate the utilization of optical networks that possess substantial capacity and exhibit minimal latency. The dynamic arrival and departure of connection requests in optical networks result in particular central links experiencing more traffic and congestion than non-central links. The occurrence of congested links leads to service blocking despite the availability of resources within the network, restricting the efficient utilization of network resources. The available algorithms in the literature that aim to balance load among network links offer a trade-off between blocking performance and algorithmic complexity, thus increasing service provisioning time. This work proposes a dynamic routing-based congestion-aware routing, modulation, core, and spectrum assignment (RMCSA) algorithm for space division multiplexing elastic optical networks (SDM-EONs). The algorithm finds alternative candidate paths based on real-time link occupancy metrics to minimize blocking due to link congestion under dynamic traffic scenarios. As a result, the algorithm reduces the formation of congestion hotspots in the network owing to link-betweenness centrality. We have performed extensive simulations using two realistic network topologies to compare the performance of the proposed algorithm with relevant RMCSA algorithms available in the literature. The simulation results verify the superior performance of our proposed algorithm compared to the benchmark Yen's K-shortest paths and K-Disjoint shortest paths RMCSA algorithms in connection blocking ratio and spectrum utilization efficiency. To expedite the route-finding process, we present a novel caching strategy that allows the proposed algorithm to demonstrate a much-reduced service delay time compared to the recently developed adaptive link weight-based load-balancing RMCSA algorithm.