Belden Incorporated is an American manufacturer of networking, connectivity, and cable products. The company designs, manufactures, and markets signal transmission products for demanding applications. These products serve the industrial automation, enterprise, security, transportation, infrastructure, and residential markets. Belden is one of the largest U.S.-based manufacturers of high-speed electronic cables primarily used in industrial, enterprise, and broadcast markets.
The design and optimization of large antenna arrays and Reconfigurable Intelligent Surfaces (RIS) have become critical for emerging wireless communication systems, including 5G and 6G networks. Although technologies such as Massive Multiple Input Multiple Output (MIMO) and RIS offer unprecedented opportunities for enhanced coverage, improved spectral efficiency, and adaptive propagation environments, the corresponding electromagnetic structures often present extremely large and complex design spaces that require exhaustive exploration to achieve optimal performance. As a result, achieving goals such as miniaturization, bandwidth enhancement, improved scattering characteristics, or precise phase control becomes a major focus when working with these complex spaces. In this paper, we introduce a systematic methodology for developing an optimization framework dedicated to planar electromagnetic structures using binary pixelization of the conducting surface. By discretizing the design region into a matrix of metallic and non-metallic pixels, the approach enables flexible topology manipulation while maintaining compatibility with full-wave simulation tools. We then couple this representation with heuristic optimization methods, specifically Genetic Algorithms (GA) and Surrogate-Assisted Differential Evolution for Antenna (SADEA) optimization approaches, to efficiently navigate the high-dimensional search space and identify high-performance designs aligned with target specifications. This paper describes the implementation of this workflow in MATLAB, detailing the generation of pixelized geometries, their integration into simulation routines, the formulation of fitness functions, and their integration with the optimization tools. The complete MATLAB codes, along with supporting user interface and examples, are made publicly available via GitHub to facilitate reproducibility and encourage further research in computational design of advanced planar structures.
The advent of large-scale quantum computers poses a significant threat to contemporary network security protocols, including Wi-Fi Protected Access (WPA)-Enterprise authentication. To mitigate this threat, the adoption of Post-Quantum Cryptography (PQC) is critical. In this work, we investigate the performance impact of PQC algorithms on WPA-Enterprise-based authentication. To this end, we conduct an experimental evaluation of authentication latency using a testbed built with the open-source tools FreeRADIUS and hostapd, measuring the time spent at the client, access point, and RADIUS server. We evaluate multiple combinations of PQC algorithms and analyze their performance overhead in comparison to currently deployed cryptographic schemes. Beyond performance, we assess the security implications of these algorithm choices by relating authentication mechanisms to the quantum effort required for their exploitation. This perspective enables a systematic categorization of PQ-relevant weaknesses in WPA-Enterprise according to their practical urgency. The evaluation results show that, although PQC introduces additional authentication latency, combinations such as ML-DSA-65 and Falcon-1024 used in conjunction with ML-KEM provide a favorable trade-off between security and performance. Furthermore, we demonstrate that the resulting overhead can be effectively mitigated through session resumption. Overall, this work presents a first real-world performance evaluation of PQC-enabled WPA-Enterprise authentication and demonstrates its practical feasibility for enterprise Wi-Fi deployments.
Industrial networks are becoming increasingly complex due to rising connectivity demands, real-time requirements, and cross-domain integration challenges. These changes require efficient and adaptive configuration and management solutions. State-of-the-art tools depend on manual configurations or rigid rule-based automation, limiting scalability and responsiveness. This paper presents a Flow-Based Programming (FBP) approach using Node-RED to enable flexible, event-driven network automation. By integrating Information Technology (IT) and Operational Technology (OT) components, our framework enhances both security and operational safety, reduces manual intervention, and ensures consistent policy enforcement. We demonstrate its effectiveness through two industrial use cases—automated port lockdown for secure access control and automated software updates for Automated Guided Vehicles (AGVs), showcasing its potential to streamline network management and reduce operational downtime.
