The advent of the 6G and B6G networks marks a turning point in the development of the global interconnected environment. In the case of B6G we see the introduction of what may be very revolutionary services like the ‘touch internet’ and ‘holographic communications’. Also, we note that in addition to size and complexity, which are at present unprecedented, the new networks also have very high performance requirements of ultra-low latency, high reliability, and support for up to hundreds of millionsof devices. Also, we see that the traditional, centralized management approach is in large part what is breaking down in the new networks. The central approach which is also very rigid and prone to failure is what is leaving new networks in the dust as they try to deal with their dynamic complexity.
In this context, this special issue focuses on the “fully autonomous network” paradigm, which envisions the metamorphosis of future networks into self-driving, self-enriching, and self-healing networks. Such networks are anticpaited to be realized via a seamless integration of artificial intelligence (AI), edge computing (EC), and cloud computing (CC), which gives it elastic, intelligent, and power-saving infrastructure. Hence, facilitating instantaneous adaptation, proactive control, and automated recovery from unplanned outages and security risks.
Rationale and Challenges
- Complexity Catastrophe: The exponential growth of devices, base stations, and network slices in 6G/B6G networks, creates an ultra-complex system, in which, human intervention for control purposes is not possible.
- Temporal and Resource Challenges: Autonomous driving, extended reality, and industrial automation applications often require decisions at the microsecond level. Hence, intelligence needs to be distributed near the network’s edge.
- Resilience and Reliability: It’s widely accepted that mission-critical applications would require “six-nines” (99.9999%) reliability. This means that future networks must continuously predict, prevent, and mitigate failures, cyberattacks, and QoS degradation. All of these must be done without human intervention.
- Sustainability Imperative: The design of autonomous networks must take into account the sustainability as world focus turns to green energy and reducing environmental impact. Hence, which resources to be used and how energy consumption is reduced will be major aspect in such networks.
Main Objectives
This special issue focuses mainly on four themes:
- AI automation: Employ advanced AI for the management of networks in an explainable and trusted manner.
- Distributed Intelligence: Seamless collaboration between cloud and edge devices is enabled.
- Personal Healing and Sustainability: Building networks capable of automatically healing & having efficient power use.
- Security & Ethics: Addressing new AI threats and ensuring ethical, unbiased, and secure operations.
Target Audience and Expected Impact
This special issue could be a suitable venue for publication for the following contributors:
- Academic researchers who focus on the theory and algorithms for intelligent autonomy in networks.
- Experts from the telecom operators, hardware manufacturers, and cloud vendors are influencing the architecture of the new-generation 6G networks.
- Current standards and policy-making organizations (such as 3GPP, ITU, and ETSI) are looking for input on the technical, ethical, and broader societal implications of fully autonomous networks.
By converging theory and practice, this issue aims to facilitate the development of an integrated roadmap for intelligent, robust, and sustainable communication networks. Autonomic networks will be the building blocks of the interconnected world ahead of us, enabling society to have a communications infrastructure that is faster, smarter, and automatically adaptive, secure, and sustainable.
Topics of Interest
- Self-healing and fault-tolerant network architectures.
- AI-driven zero-touch network management.
- Federated and distributed learning for network optimization.
- Edge-cloud synergy and task offloading strategies.
- Trust, safety, and security in autonomous network control.
- Digital twin models for predictive network maintenance.
- Blockchain for decentralized orchestration and transparency.
- Energy-aware adaptive network operation.
- Network slicing and dynamic resource allocation for 6G.
- Reinforcement learning for end-to-end network automation.
Benefits of submitting by the deadline
- No article processing charges
- Complimentary language editing
For further details, please contact the editorial office at: info@scifiniti.com
