With the growth of traffic volume and the emergence of various new applications, future telecom networks are expected to be increasingly heterogeneous with respect to applications supported and underlying technologies employed. To address this heterogeneity, it may be most cost effective to set up different lightpaths at different bit rates in such a backbone telecom mesh network employing optical wavelength-division multiplexing. This approach can be cost effective because low-bit-rate services will need less grooming (i.e., less multiplexing with other low-bit-rate services onto high-capacity wavelengths), while a high-bit-rate service can be accommodated directly on a wavelength itself. Optical networks with mixed line rates (MLRs), e.g., 10/40/100 Gb/s over different wavelength channels, are a new networking paradigm. The unregenerated reach of a lightpath depends on its line rate. So, the assignment of a line rate to a lightpath is a tradeoff between its capacity and transparent reach. Thus, based on their signal-quality constraints (threshold bit error rate), intelligent assignment of line rates to lightpaths can minimize the need for signal regeneration. This constraint on the transparent reach based on threshold signal quality can be relaxed by employing more advanced modulation formats, but with more investment. We propose a design method for MLR optical networks with transceivers employing different modulation formats. Our results demonstrate the tradeoff between a transceiver's cost and its optical reach in overall network design.

The unprecedented advancement of Artificial Intelligence (AI) has positioned Explainable AI (XAI) as a critical enabler in addressing the complexities of next-generation wireless communications. With the evolution of the 6G networks, characterized by ultra-low latency, massive data rates, and intricate network structures, the need for transparency, interpretability, and fairness in AI-driven decision-making has become more urgent than ever. This survey provides a comprehensive review of the current state and future potential of XAI in communications, with a focus on network slicing, a fundamental technology for resource management in 6G. By systematically categorizing XAI methodologies–ranging from model-agnostic to model-specific approaches, and from pre-model to post-model strategies–this paper identifies their unique advantages, limitations, and applications in wireless communications. Moreover, the survey emphasizes the role of XAI in network slicing for vehicular network, highlighting its ability to enhance transparency and reliability in scenarios requiring real-time decision-making and high-stakes operational environments. Real-world use cases are examined to illustrate how XAI-driven systems can improve resource allocation, facilitate fault diagnosis, and meet regulatory requirements for ethical AI deployment. By addressing the inherent challenges of applying XAI in complex, dynamic networks, this survey offers critical insights into the convergence of XAI and 6G technologies. Future research directions, including scalability, real-time applicability, and interdisciplinary integration, are discussed, establishing a foundation for advancing transparent and trustworthy AI in 6G communications systems.

Quantum Key Distribution (QKD) is a promising technology that provides proven unconditional security based on fundamentals of quantum physics, especially for point-to-point communications. It could be applied in large-scale optical networks for long-distance key provisioning mainly by three relaying methods: quantum-repeater-based QKD, trusted-relay-based QKD, and measurement-device-independent QKD (MDI-QKD). However, quantum-repeater-based QKD is still under study because of the immature technologies such as the preliminary quantum memory. The trusted-relay-based QKD is vulnerable since insecurity of non-ideal single-photon sources and detectors cannot be ignored in practical applications. On the other hand, for MDI-QKD, there exists a limitation on its key rate under long-distance communications. According to these limitations, embedding protocols like MDI-QKD into the existing trusted-relay-based QKD secured optical networks (QKD-ON) with usage of untrusted relays is a promising key-provisioning scheme. In this paper, we study such partially-trusted relay scenarios and focus on its routing of keys in different kinds of typical network topologies. A partially-trusted-relay-based QKD method is described, which can allow a pair of optical nodes sharing secret keys under the coexistence of trusted relays and untrusted relays. The secret-key provisioning with collaborative routing ( SKP-CR ) algorithm is proposed to search for the optimal key-relay routing path. We perform the simulations with different proportion of trusted relays versus untrusted relays, initial secret keys in the quantum key pools (QKPs), and traffic load. The simulations verify that the SKP-CR algorithm can significantly outperform the conventional trusted-relay-based scheme in terms of key-distribution success rate with an improvement of up to 62% with a mesh topology.

Security and privacy of patients’ data is a major concern in the healthcare industry. In this paper, we propose a system that activates robust security and privacy of patients’ medical records as well as enables interoperability and data exchange between the different healthcare providers. The work proposes the shift from patient’s electronic health records being managed and controlled by the healthcare industry to a patient-centric application where patients are in control of their data. The aim of this research is to build an Electronic Healthcare Record (EHR) system that is layered on the Ethereum blockchain platform and smart contract in order to eliminate the need for third-party systems. With this system, the healthcare provider can search for patient’s data and request the patients’ consent to access it. Patients manage their data which enables an expedited data exchange across EHR systems. Each patient’s data are stored on the peer-to-peer node ledger. The proposed patient-centric EHR platform is cross-platform compliant, as it can be accessed via personal computers and mobile devices and facilitates interoperability across healthcare providers as patients’ medical records are gathered from different healthcare providers and stored in a unified format. The proposed framework is tested on a private Ethereum network using Ganache. The results show the effectiveness of the system with respect to security, privacy, performance and interoperability.

With increasing energy consumption of the Internet, it is now imperative to design energy-efficient network architectures and protocols. Optical technologies have significant promise in improving the energy efficiency of network infrastructures. Future optical backbone networks will be heterogeneous in nature where a single link may carry various line-rate signals. This mixed-line-rate (MLR) network architecture is shown to be cost effective in satisfying heterogeneous traffic demands. In this study, we present mathematical models that can act as references for designing energy- and cost-efficient MLR optical networks. We also perform a comparative study of the energy efficiency of MLR and special cases of MLR design, named as single-line-rate networks (where all the links have same line rates). We explore the scenarios where the MLR networks minimize energy consumption. Finally, we investigate the relationship between energy-minimized and cost-minimized MLR network design.