Power Consumption-Aware Asymmetrical Traffic Splitting in SEON Based on Traffic Demands

In survivable elastic optical networks (SEON), state aware asymmetrical splitting traffic demand (ASTD) is a multipath protection scheme highlighted in existing literature. This approach optimally splits the total traffic demand into unequal parts and uses link-disjoint multiple (LDM) paths with state-aware allocation (SAA) strategies to transmit each part. Integrating distance-adaptive modulation can further enhance network performance by lowering the probability of blocking and reducing Power Consumption (PC). This paper proposes a Power Consumption-aware Asymmetrical Traffic (PCAT) splitting model that optimally asymmetrically splits traffic demands into multiple link disjoint available paths. By leveraging distance adaptive modulation, the model aims to improve the connection acceptance rate (CAR), reduce blocking probability (BP) and lower PC. The PCAT splitting model is tailored for heterogeneous traffic demands and determines the optimal number of traffic demand splitting. Simulations on varied real-world networks showed that the proposed model significantly reduces PC with respect to the previous state-aware ASTD model of the literature. This means that the performance of networks is considerably better because of the improvement in power efficiency by the PCAT splitting model while concurrently maintaining a low BP.