Overview
This is a call for original research contributions to a special issue of the Journal of Computer Networks and Communications (JCNC) focusing on recent advancements in machine learning (ML) for unmanned vehicle networks (UVNs). This special issue aims to highlight the growing significance of ML techniques in enhancing the capabilities of autonomous networks formed by aerial, ground, or underwater vehicles.
Background & Relevance
Unmanned Vehicle Networks represent a critical area of research, particularly as applications in civil sectors such as delivery services, environmental monitoring, and disaster management continue to expand. Traditional optimization models often fall short in addressing the complexities and challenges posed by these emerging applications, especially in dynamic environments. Machine learning offers a promising alternative, allowing for adaptive strategies that can improve the performance and reliability of UVNs. The exploration of cooperative behaviors among swarms of autonomous vehicles is particularly under-researched, making this a vital area for further inquiry.
Key Details
- Submission Deadline: January 10, 2020
- Publication Date: May 2020
- Topics of Interest:
- Modeling and analysis of cooperative systems in UVNs
- Nature-inspired mobility management algorithms
- Deep, unsupervised, and reinforcement learning applications
- ML-inspired network architecture and protocols
- Data analysis from UVN-aided IoT systems
- Crowdsensing systems utilizing UVNs
- Continual learning and adaptation strategies
- Edge computing for real-time ML execution
- Energy-efficient solutions for UVNs
- Submission Link: Manuscript Tracking System
Eligibility & Participation
This call for papers is open to researchers and practitioners in the fields of machine learning, robotics, and networking. Contributions that explore interdisciplinary approaches to the challenges faced by UVNs are especially encouraged.
Submission or Application Guidelines
Authors interested in contributing should prepare their manuscripts according to the journal’s submission guidelines and submit them through the Manuscript Tracking System provided in the key details section. All submissions will undergo a peer-review process, and accepted papers will be published upon acceptance, irrespective of the special issue’s publication date.
Additional Context / Real-World Relevance
The integration of machine learning into unmanned vehicle networks is poised to transform various industries by enhancing operational efficiency and enabling innovative applications. As the demand for autonomous systems grows, understanding the interplay between machine learning and networking will be crucial for developing robust solutions that can operate in real-world scenarios.
Conclusion
Researchers are encouraged to explore this opportunity to contribute to a significant area of study that combines machine learning with unmanned vehicle networks. By submitting your work, you can help advance the field and contribute to the development of smarter, more efficient autonomous systems.
Category: CFP & Deadlines
Tags: machine learning, unmanned vehicle networks, autonomous systems, networking, deep learning, reinforcement learning, IoT, energy efficiency
