Special Issue "Statistical Approaches for Reliability of Future Communication Systems and Networks"
Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 2545
Interests: network management; network security; availability; 5G; NFV
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Special Issue in Future Internet: Anomaly Detection in Modern Networks
Interests: statistics; reliability; availability; Bayesian statistics; stochastic processes
Interests: network dependability modeling and evaluation; network performance analysis; network resource orchestration; network security
Interests: dependability benchmarking; software fault injection testing; virtualization reliability; safety-critical systems
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
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