In SDN-enabled disaggregated optical networks, switches and wavelength converters are managed through software abstractions that model their capabilities, enabling greater flexibility and improved performance. While traditional approaches statically assign converters to specific nodes, such abstractions allow wavelength conversion to be considered as a distributed processing function, dynamically migrating across the network like a Cloud-based service. This enhances the ability of the control layer to flexibly allocate conversion resources to reduce blocking occurrences. Additionally, the orchestration layer dynamically selects wavelength allocation policies based on these abstractions, ensuring an optimal balance between performance and resource efficiency. This paper proposes a novel Cloud-native approach to wavelength conversion in disaggregated optical networks. We present a framework for orchestrating and controlling end-to-end services with a focus on lightpath provisioning, supported by a resource availability model that facilitates efficient wavelength selection. Our evaluation compares multiple wavelength assignment algorithms through both static and dynamic simulations. The results highlight key trade-offs among these algorithms in terms of blocking probability, resource utilization, and overall cost efficiency, providing valuable insights for improving the overall network performance.

Physical layer security is a crucial step towards fully secure communications systems. The flexibility and ubiquity of digital signal processors in modern wireless and optical communication systems open up a clear path for the development of discrete-signals encryption techniques, which can be implemented relatively cheap. In this paper, we show the fundamental role of amplitude and phase encoding in the security and practical implementation of linear discrete signal cryptography (DSC). We focus on the spectral implementation of these encoding schemes and consider the equivalence between spectral amplitude encoding (SAE) and spectral scrambling (SS). Numerical simulation results show that 16-quadrature amplitude modulation (16-QAM) signals encrypted by SS and spectral phase encoding (SPE) can be recovered only if eavesdroppers know the exact position of ~95% of the scrambled samples with a maximum phase error of ± 7° for all samples. The number of brute force attacks to break such encrypted signals far exceeds the one provided by the widely deployed data ciphering algorithm Advanced Encryption Standard (AES). Physical layer results reveal that the bit error ratio (BER) associated with the encrypted signals is 0.50 regardless of the deployed signal format and DSC scheme. The BER vs. signal-to-noise ratio performance of the encrypted/ decrypted signal is the same as that of signals not encrypted. Finally, the paper proposes the adoption of pseudo-random dynamic keys (PRDKs) to encrypt signals. The paper also investigates the use of pseudo-random dynamic keys (PRDKs) to promote encryption randomness, diffusion, and confusion to the encrypted signals. A new numerical methodology shows this strategy outperforms AES diffusion and confusion properties.

System reliability of a multistate flow network can be computed in terms of all the lower boundary points, called d-minimal paths (d-MPs). Although several algorithms have been proposed in the literature for the d-MP problem, there is still room for improvement upon its solution. Here, some new results are presented to improve the solution of the problem. A simple novel algorithm is improved to solve a Diophantine system that appeared in the d-MP problem. Then, an improved algorithm is proposed for the d-MP problem. It is also explained how the proposed algorithm can be used in order to assess the reliability of some smart grid communication networks. We provide the complexity results and show the main algorithm to be more efficient than the existing ones in terms of execution times through some benchmark networks and a general network example. Moreover, we compare the algorithms through one thousand randomly generated test problems using the Dolan and More's performance profile.

This paper proposes a methodology to compare scheduling algorithms for congestion resolution in optical burst switching or optical packet switching networks, focusing on the issue of wavelength conversion capabilities. The performance of such algorithms when full wavelength conversion is available at the switching nodes are compared with the case of conversion capabilities over a limited range of wavelengths. The results presented show that limited range wavelength conversion is not necessarily performing worse than full wavelength conversion, as long as the correct terms of comparison are considered.

One of the great challenges nowadays when managing IP networks is to guarantee proper Quality of Service, using network infrastructure on optimized way. One of the proposed solutions is traffic engineering with MPLS. However, the characterization of the demands and of the network state are difficult tasks, considering that the demands and the data traffic are random, consequently, the network state changes dynamically and in a random way. In this work we propose a connection admission controller that uses fuzzy logic based on linguistic rules to treat the inaccurate information in IP over MPLS networks with the purpose of offering Quality of Service to the users. In accordance with the simulation results, we concluded that the use of fuzzy logic allows a large flexibility in the connection admission process and the possibility to include more network and traffic information when making a decision without increasing considerably the controller complexity.