Advances in Network Automation and Self-Organizing Networks: Architecture, Algorithms, and Applications
Special Issue Editors
Interests: agent-based systems; edge computing; self-organizing clouds
Special Issue Information
Dear Colleagues,
Network self-organization is a paradigm shift in network management as it seeks to empower networks with the capability to adapt to changing conditions autonomously, without the need for human intervention. However, this vision entails several challenges that must be overcome by researchers and practitioners to realize its full potential. One such challenge lies in the development of effective models and algorithms that can accurately capture the behavior of complex network environments and enable automated decision making in a distributed and dynamic manner. This requires a deep understanding of the underlying network topology, traffic patterns, and performance metrics, as well as the ability to develop sophisticated optimization techniques that can balance competing objectives and constraints. The complexity of modern communication networks, which often involve large-scale, heterogeneous, and dynamic environments, exacerbates this challenge, necessitating the design of advanced algorithms that can adapt to changing conditions in real time.
Another key challenge is the need for robust mechanisms for controlling and coordinating the behavior of large-scale networks, particularly in the context of emerging technologies such as the Internet of Things (IoT) and smart cities. In these environments, the sheer scale and diversity of networked devices, coupled with their dynamic and unpredictable behavior, pose significant challenges for network management. Developing scalable and fault-tolerant architectures that can adapt to changing conditions and failures is therefore an important research direction in this area.
Moreover, it is apparent that practical applications and use cases are needed to demonstrate the value of network automation and self-organization in real-world scenarios. While theoretical advances in this field are important, it is ultimately through concrete implementations and deployments that the benefits of network self-organization can be realized.
This Special Issue will serve as a catalyst for research and innovation in network self-organization by identifying key challenges and opportunities for future development. We aim to bring together researchers and practitioners from academia, industries, and governments to share their latest findings and insights on this topic. We welcome original research papers that contribute to the state of the art in network automation and self-organizing networks. Potential topics include (but are not limited to) the following:
- Novel architectures for self-organizing networks;
- Advanced algorithms for topology adaptation and optimization;
- Distributed control and coordination in self-organizing networks;
- Artificial intelligence and machine learning for network management;
- Agent-based self-organizing and self-managing networks;
- Practical applications of self-organizing networks, such as smart cities and IoT deployments.
Dr. Dapeng Dong
Dr. Jun (John) Huang
Guest Editors
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Keywords
- distributed control
- self-organization
- network resilience
- AI for network management
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