Dear Colleagues,

Reliability aspects are of increasingly crucial importance across the hyperconnected technological world.

All modern paradigms and architectures, such as Cloud/Fog/Edge Computing, the Internet of Things, 5G/6G, Network Function Virtualization, and Network Slicing, must satisfy strict reliability and availability requirements to provide their services without interruption. Consequently, characterizing a technological system or a network architecture in terms of its ability to deal with anomalous events (e.g., faults, attacks, overload, and disaster) and recovering its functionalities is becoming a key issue. Different methodologies are useful to achieve this aim—from the classic statistical methods to the data-driven approaches—including modern deep learning techniques.

Due to the growing interest both of academia and industry in the broad field of Reliability Engineering, for this Special Issue, we encourage high-quality research contributions—both theoretical and experimental—and timely survey papers that pinpoint future research directions in this field.

Topics of interest include, but are not limited to, the following:

• Reliability, dependability, availability, performability, serviceability, maintainability, and resiliency for emerging network and system architectures;
• Statistical methods for reliability and availability evaluation of emerging networks and systems;
• Next-generation network survivability;
• Reliability/availability aspects in the field of softwarized networks (NFV, SDN, and Network Slicing);
• Maintainability for emerging networks and systems;
• Data analysis for testbeds of emerging networks and systems;
• Prognostics and health management techniques for future networks and systems;
• Network and system resilience;
• Fault detection and isolation in large-scale networks;
• Anomaly detection techniques for networks and systems;
• Reliability issues of communication protocols;
• Fault tolerance techniques for emerging network architectures;
• Design of dependable architectures;
• Statistical learning for reliability assessment;
• Machine learning and Artificial Intelligence techniques for reliability;
• Fault diagnosis and prediction in future networks;
• Algorithms for reliability of networks and systems;
• High Availability issues in 5G/6G networks;
• High Availability issues in Cloud/Fog/Edge Computing;
• High Availability for IoT and sensors;
• High Availability for vehicle-to-vehicle communication;
• High availability/Costs/Energy consumption trade-off for emerging network and systems;
• Reliability aspects for emerging paradigms (Industrial IoT, Smart and Green Environments, Industry 4.0);
• Ultra-Reliable Services (6 nines and beyond);
• Chaos Engineering for future network infrastructures;
• Load, stress, and fault-injection testing for network services;
• Fault localization and debugging in network services.

Dr. Mario Di Mauro
Prof. Dr. Fabio Postiglione
Prof. Dr. Besmir Tola
Dr. Luigi De Simone
Prof. Dr. Roberto Natella
Guest Editors

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