CAMAD 2020

IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks
September 14-16, 2020
Pisa, Italy

Submissions Due: May 20, 2020

The foundation of 5G and beyond mobile networks lies in the convergence between networking and computing. The most appealing realization of such convergence is the application of artificial intelligence (AI) and machine learning (ML) to optimize network functions. The latter has generated an increasing interest from academia and industry paving the path for the transformation from the 5G paradigm “connected things” into a “connected intelligence” vision for beyond 5G and 6G mobile networks. To this end, the role of AI/ML is to support zero-touch configuration and orchestration, thereby enabling self-configuration and self-optimization of the mobile network. Mobile networks are indeed becoming increasingly complex, heterogeneous, dynamic and dense, which makes extremely hard to model correctly their behavior. Model-free solutions that AI enable can overcome such challenge.

This Special Session seeks contributions from experts in areas such as network programming, distributed systems, machine learning, data science, data structures and algorithms, and optimization to discuss the latest research ideas and results on the application of AI/ML to networking. Specifically, this Special Session welcomes contributions in the following major areas (indicative list, other related topics will also be considered):

– Machine learning (ML) and big data analytics in networking
– Case studies showing (dis)advantages of AI/ML techniques for networking over traditional ones
– Edge-driven data analytics and applications to smart cities
– AI/ML assisted network optimization
– Resource-efficient machine learning for mobile networks
– Measurements and analysis of network traffic for AI/ML systems
– Efficient ML data structures, algorithms and network protocols to process network monitoring data
– Approaches for privacy-aware network traffic data collection
– Architectures for federated learning and its applications to networking
– Energy-efficient federated learning
– Incentive mechanisms of federated learning
– In-network computation for next generation wireless networks

IMPORTANT DATES
Paper Submission Deadline: May 20, 2020
Author Notification: July 3, 2020
Camera Ready: July 31, 2020